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Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

How do data scientists frame their relations with domain experts? This study focuses on data scientists' aspired professional jurisdiction and their multiple narratives regarding data science's relations to other fields of expertise. Based on the analysis of 60 open-ended, in-depth interviews with data scientists, data science professors, and managers in Israel, the findings show that data scientists institutionalize three narratives regarding their relations with domain experts: (a) replace experts, (b) absorb experts' knowledge, and (c) provide a service to experts. These three narratives construct data scientists' expertise as universal and omnivorous; namely, they are relevant to many domains and allow data scientists to be flexible in their claim for authority. [ABSTRACT FROM AUTHOR]

When it comes to relationships with technology, questions of trust and trustworthiness are never far away. This paper explores how the rapid expansion of Artificial Intelligence (AI) technologies into people’s everyday lives pushes the question of what it means to trust technology into new and unfamiliar territories, far beyond traditional frameworks associated with either functional reliability (subject-object), or those that take their inspiration from interpersonal (subject-subject) relations. Challenging the cognitivist and humanist emphases of such models of trust, the paper instead develops a more ontological sense of trust which foregrounds the complex material processes and unconscious forces that shape how people think and relate to AI. Drawing on in-depth interviews with users of AI-enabled navigation apps (like Google Maps and Waze), we draw out these ontological dimensions of trust in three main ways. First, how relationships with these technologies are strongly shaped by imaginaries that have significant performative impacts on how AI is conceived and whether and how it can be trusted. Second, how people’s sense of trust is often attuned to the broader socio-technical ecologies that shape AI’s existence. And finally, how the affective force of everyday habits enables or constrains trust in relation to specific contexts and scenarios. [ABSTRACT FROM AUTHOR]

Background: Digital platforms are involved in a reconfiguration of imaginaries surrounding the prediction of homosexuality. Analysis: This article analyzes three technoscientific controversies. The first addresses the prediction of users' sexual orientation based on the content they like on Facebook. The second deals with facial recognition software aimed at predicting homosexuality. Finally, the third focuses on the alleged ability of TikTok's algorithms to influence the sexual orientation of its users. Conclusion and implications: Analyzing the diverse imaginaries around prediction allows us to understand the concerns that various social actors share about artificial intelligence and its implications for LGBTQ+ communities. [ABSTRACT FROM AUTHOR]

Copyright of Studii de Ştiintă şi Cultură is the property of Studii de Stiinta si Cultura and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article conducts a 20-year review of studies investigating the utilization of artificial intelligence in HVAC (Heating, Ventilation, and Air Conditioning) system control, with a particular focus on automotive HVAC systems, renowned for their unique challenges due to the highly dynamic nature of automotive cabins. Artificial neural networks (ANNs) provide adaptive modeling and control capabilities to enhance energy efficiency, thermal comfort, and air quality in HVAC systems. Nevertheless, ANNs exhibit limitations, primarily their performance being constrained by training data, impeding adaptability to unforeseen scenarios. To overcome these constraints, researchers have explored hybrid approaches that integrate ANNs with PID (Proportional, Integral, and Derivative) or PI (Proportional and Integral) algorithms, resulting in systems referred to as Neuro-PID or Neuro-PI. These systems can effectively handle unanticipated situations by absorbing errors introduced by ANNs. Nonetheless, the applicability of Neuro-PID varies depending on the specific system. It becomes infeasible in scenarios with substantial delays, prompting the choice of the appropriate approach based on the controllability factor, a ratio between system delay and time constant. A controllability factor less than 2 indicates the suitability of employing ANNs for PID controller tuning. Furthermore, the intricate interaction between temperature and humidity in HVAC control systems diminishes the effectiveness of traditional PID. To proficiently regulate both variables, a viable alternative is the amalgamation of ANNs with specific control logic or the deployment of distinct ANN algorithms for varying scenarios. The heightened variability and unpredictability within automotive HVAC systems, driven by continuous vehicle movement and door/window operations, present additional challenges. In such contexts, reinforcement learning techniques have found application, allowing systems to dynamically adapt to unforeseen events. In summary, the choice of HVAC control approach hinges on the primary goal—thermal comfort or specific variable control—as well as the system's noise level, controllability factor, and system nature. While ANNs hold significant potential, combining them with other techniques, such as PID, reinforcement learning, or specific control logic, may prove essential in addressing the intricacies of HVAC systems [ABSTRACT FROM AUTHOR]

This study aimed to design an autodelineation model based on convolutional neural networks for generating high-risk clinical target volumes and organs at risk in image-guided adaptive brachytherapy for cervical cancer. A novel SERes-u-net was trained and tested using CT scans from 98 patients with locally advanced cervical cancer who underwent image-guided adaptive brachytherapy. The Dice similarity coefficient, 95th percentile Hausdorff distance, and clinical assessment were used for evaluation. The mean Dice similarity coefficients of our model were 80.8%, 91.9%, 85.2%, 60.4%, and 82.8% for the high-risk clinical target volumes, bladder, rectum, sigmoid, and bowel loops, respectively. The corresponding 95th percentile Hausdorff distances were 5.23 mm, 4.75 mm, 4.06 mm, 30.0 mm, and 20.5 mm. The evaluation results revealed that 99.3% of the convolutional neural networks-generated high-risk clinical target volumes slices were acceptable for oncologist A and 100% for oncologist B. Most segmentations of the organs at risk were clinically acceptable, except for the 25% sigmoid, which required significant revision in the opinion of oncologist A. There was a significant difference in the clinical evaluation of convolutional neural networks-generated high-risk clinical target volumes between the two oncologists (P < 0.001), whereas the score differences of the organs at risk were not significant between the two oncologists. In the consistency evaluation, a large discrepancy was observed between senior and junior clinicians. About 40% of SERes-u-net-generated contours were thought to be better by junior clinicians. The high-risk clinical target volumes and organs at risk of cervical cancer generated by the proposed convolutional neural networks model can be used clinically, potentially improving segmentation consistency and efficiency of contouring in image-guided adaptive brachytherapy workflow. [ABSTRACT FROM AUTHOR]

This paper examines the problem of hallucinations in four scientific articles generated by ChatGPT-4 from various sub-fields of business administration. Specifically, the aim is to check whether the references generated by ChatGPT exist and, if this is the case, whether they are correct. A first surprising result is that nearly 40 Prozent of the 174 sources referenced in the articles, whose bibliographic details were listed after the individual main chapters, were not included in the specially for each article generated bibliography. A check of the bibliographic entries revealed that between 18 % and 100 % of the sources in the individual articles could not be found with Google Scholar. Furthermore, half of the sources found were incorrect to varying degrees (wrong document type, wrong journal name, wrong page reference). On average, only a quarter of the bibliographic references were completely correct. In Web of Science, only a quarter of the sources could be verified, but most of them were correct. The above results show that ChatGPT-4 – besides ethical and legal concerns – should definitely not be used for writing scientific papers, as a large proportion of the references generated by ChatGPT (valid at the time of writing this paper) does not exist or is partially incorrect. Furthermore, it can be assumed that some of the article texts generated are also "invented" or come from unreferenced sources (plagiarism). Texts generated by ChatGPT must therefore be subject to a comprehensive review, which may not always be easy. The authors therefore agree with the recommendation of Gimpel et al. (2023) that ChatGPT should primarily be used as a supplement to writing (e. g., spell-checking, creating summaries, supporting the generation of ideas). [ABSTRACT FROM AUTHOR]

Les Printemps de la Médecine Interne sont des journées de formations pour les internistes francophones. Les cas cliniques présentés à ces journées sont complexes. Cette étude vise à évaluer les capacités diagnostiques des intelligences artificielles non spécialisées (modèles de langage) ChatGPT-4 et Bard en les confrontant aux énigmes des Printemps de la Médecine Interne. Les cas cliniques des Printemps de la Médecine Interne 2021 et 2022 ont été soumis à deux modèles de langage : ChatGPT-4 et Bard. En cas de mauvaise réponse, une seconde tentative était offerte. Nous avons ensuite comparé les réponses des experts internistes humains à celles des intelligences artificielles. Sur les 12 cas cliniques soumis, les experts internistes ont trouvé neuf diagnostics, ChatGPT-4 trois et Bard un. Un des cas résolus par ChatGPT-4 n'a pas été résolu par l'expert interniste. Les intelligences artificielles avaient un temps de réponse de quelques secondes. À l'heure actuelle, les compétences diagnostiques de ChatGPT-4 et Bard sont inférieures à celles d'experts humains pour la résolution de cas cliniques complexes mais sont très prometteuses. Accessibles au grand public depuis peu, elles ont déjà des capacités impressionnantes, interrogeant le rôle du médecin diagnosticien. Il faudrait envisager d'adapter les règles ou les sujets des futurs Printemps de la Médecine Interne afin qu'ils ne soient pas résolus par un modèle de langage grand public. The "Printemps de la Médecine Interne" are training days for Francophone internists. The clinical cases presented during these days are complex. This study aims to evaluate the diagnostic capabilities of non-specialized artificial intelligence (language models) ChatGPT-4 and Bard by confronting them with the puzzles of the "Printemps de la Médecine Interne". Clinical cases from the "Printemps de la Médecine Interne" 2021 and 2022 were submitted to two language models: ChatGPT-4 and Bard. In case of a wrong answer, a second attempt was offered. We then compared the responses of human internist experts to those of artificial intelligence. Of the 12 clinical cases submitted, human internist experts diagnosed nine, ChatGPT-4 diagnosed three, and Bard diagnosed one. One of the cases solved by ChatGPT-4 was not solved by the internist expert. The artificial intelligence had a response time of a few seconds. Currently, the diagnostic skills of ChatGPT-4 and Bard are inferior to those of human experts in solving complex clinical cases but are very promising. Recently made available to the general public, they already have impressive capabilities, questioning the role of the diagnostic physician. It would be advisable to adapt the rules or subjects of future "Printemps de la Médecine Interne" so that they are not solved by a public language model. [ABSTRACT FROM AUTHOR]

Copyright of Anadolu Journal of Educational Sciences International (AJESI) is the property of Anadolu Journal of Educational Sciences International and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

MRI is essential in the management of brain tumours. However, long waiting times reduce patient accessibility. Reducing acquisition time could improve access but at the cost of spatial resolution and diagnostic quality. A commercially available artificial intelligence (AI) solution, SubtleMR™, can increase the resolution of acquired images. The objective of this prospective study was to evaluate the impact of this algorithm that halves the acquisition time on the detectability of brain lesions in radiology and radiotherapy. The T1/T2 MRI of 33 patients with brain metastases or meningiomas were analysed. Images acquired quickly have a matrix divided by two which halves the acquisition time. The visual quality and lesion detectability of the AI images were evaluated by radiologists and radiation oncologist as well as pixel intensity and lesions size. The subjective quality of the image is lower for the AI images compared to the reference images. However, the analysis of lesion detectability shows a specificity of 1 and a sensitivity of 0.92 and 0.77 for radiology and radiotherapy respectively. Undetected lesions on the IA image are lesions with a diameter less than 4 mm and statistically low average gadolinium-enhancement contrast. It is possible to reduce MRI acquisition times by half using the commercial algorithm to restore the characteristics of the image and obtain good specificity and sensitivity for lesions with a diameter greater than 4 mm. [ABSTRACT FROM AUTHOR]

L'intelligence artificielle (IA) se développe à une vitesse impressionnante dans le domaine de la santé. L'IA ouvre la voie à de nouvelles pratiques d'aide au diagnostic, de médecine préventive, de suivi individualisé du patient, d'appui au choix d'une thérapie, d'aide à l'interprétation de résultats d'examens complémentaires... Loin d'être une solution miracle, la délégation de tâches à l'IA soulève de nombreuses questions éthiques portant notamment sur la supervision des algorithmes, l'égalité d'accès à l'innovation et l'utilisation des données des patients. Il est encore difficile de prédire si l'IA restera un « filet de sécurité » pour le médecin ou si elle le supplantera. La France et l'Europe ont posé le principe de « garantie humaine » à l'interprétation des résultats diagnostiques et thérapeutiques, impliquant que la machine ne peut agir seule et consacrant la responsabilité du professionnel de santé. Cet article vise à comprendre à quel point l'IA est complexe à encadrer au plan juridique au risque d'en négliger le secret, que ce soit au plan individuel ou collectif. Artificial intelligence (AI) is developing at an impressive speed in the field of health. AI paves the way for new practices in diagnostic assistance, preventive medicine, individualized patient follow-up, support in choosing a therapy, assistance in interpreting the results of additional examinations, etc. Far from being a magic bullet, delegating tasks to AI raises many ethical questions relating in particular to the supervision of algorithms, equal access to innovation and the use of patient data. It is still difficult to predict whether AI will remain a "safety net" for the doctor or if it will supplant him. France and Europe have laid down the principle of "human guarantee" in the interpretation of diagnostic and therapeutic results, implying that the machine cannot act alone and enshrining the responsibility of the health professional. This article aims to understand how complex AI is to regulate legally at the risk of neglecting its secrecy, whether at the individual or collective level. [ABSTRACT FROM AUTHOR]

This research represents one of the three research axes of the doctoral thesis entitled "The Creation Of Chatbots For A French Foreign Language Class: Contributions And Limitations". Through this axis, we observed whether a significant change occurs with the use of Chatbots in the learning of French as a Foreign Language, particularly in relation to the concept of the linguistic other, a central notion within the framework of the action-oriented approach. In this article, we also presented the opinions of the learners regarding the use of the mentioned Chatbots. We created a total of eight Chatbots based on decision tree logic, incorporating objectives related to written expression at the targeted level--specifically, level B1+ derived from the complementary volume of the Common European Framework of Reference for Languages (CEFR) (2020). A descriptive qualitative study was employed to achieve the objectives of this research. To carry out our research, we implemented the development research method. The study took place during the spring semester of the academic year 2021-2022 and was limited to level B1+, involving 12 learners who chose the written expression course in the second semester of the first year of the Bachelor's program in the Department of French as a Foreign Language at the Faculty of Education of Anadolu University. According to the research results, we can observe that the vast majority of learners were satisfied with the use of Artificial Intelligence, specifically Chatbots, in their courses. The sense of reality, particularly the perception of correspondence with the Other, a francophone in our case, was strong enough to ensure a certain natural aspect of the conversation. [ABSTRACT FROM AUTHOR]

This article examines the advancement of automated fact-checking in Brazil and investigates how artificial intelligence (AI) products shape publishers' discourses and practices. First, it maps the field to identify how it has evolved throughout the years. Next, it draws on 30 official statements published by journalists and their tech partners, and seven semi-structured interviews with representatives from five websites. This article shows an emerging automation landscape in the Brazilian fact-checking venture supported by the tech industry. Nonetheless, AI has challenged fact-checkers' authority and increased the technologists' influence over journalism. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is a rapidly expanding field of research. Its applications concern all human activities. It can be used in particular to improve the speed and precision of diagnosis and screening of diseases and facilitate clinical care. It could facilitate access to health services in countries or rural communities where patients often struggle to access health resources. But as with any technology, it can also be misused and AI can lead to harmful effects. The WHO, in its "First global report on artificial intelligence (AI) applied to health and guiding principles for its design and use" highlights that these opportunities are linked to challenges and risks, including unethical collection and use of health-related data, biases introduced into algorithms, and risks to patient safety, cybersecurity, and the environment [1]. AI in health must be used ethically, transparently and in complement to human skills to maximize its advantages while minimizing its disadvantages. So what is AI and conversational AI? What are its operating modes and performance? On what fundamental ethical principles should we exercise vigilance? [ABSTRACT FROM AUTHOR]

Copyright of Íkala: Revista de Lenguaje y Cultura is the property of Universidad de Antioquia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Pathology is the property of Canadian Association of Pathologists and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The notion of artificial intelligence (AI) was born in the twentieth century, and many AI researchers have been promising us better days by integrating AI into our personal and professional lives. However, in recent years, as a result of technological developments, we have been faced with a massive intrusion of AI into our daily lives. AI allows us to analyse massive quantities of medical data in order to create algorithms to help diagnose and treat male infertility. However, the use of AI in andrology and more generally in the healthcare field also presents challenges. Confidentiality of medical data and legal liability in the event of algorithmic errors or biases are major concerns. In addition, it is essential to ensure that AI does not completely replace human medical expertise, but rather complements it to provide the best possible care for patients. [ABSTRACT FROM AUTHOR]

Many contemporary artists are rehabilitating the historical device of the natural history diorama by creating immersive installations designed to construct ecosystems. In particular, this article examines some of Pierre Huyghe's works made since 2010, which present autopoietic ecosystems composed of both organic and technological elements. By comparing the workings and purposes of the historical diorama and aquarium, this article aims to show how Pierre Huyghe's immersive installations decentralise the viewer from a dominant position in relation to what is exhibited. In this way, Huyghe attacks the Western separation between nature and culture by hijacking the workings of the diorama itself. [ABSTRACT FROM AUTHOR]

Optimization of the adenoma detection rate (ADR), inversely proportional to the risk of interval colorectal cancer, is a major objective in colorectal cancer (CRC) screening. Achieving optimal ADR involves not only adherence to best practice guidelines but also benefits from technological advancements and developments in endoscope technology. Best practices with demonstrated positive impact on ADR include ensuring strict adherence to a residue-free diet for at least 24 hours (by increasing patient awareness or even offering "pre-packaged diets"), promoting split-dose bowel preparation, scheduling dedicated and sufficiently long operating sessions, systematically using a washing pump, maintaining an adequate colon exploration time, and performing a double exploration of the right colon, preferably with cecal retrovision. Adhering to these best practices enables achieving high-quality patient preparation, completeness of colonoscopies, and ultimately a sufficiently high ADR. On the other hand, optimization devices developed in recent years, which have shown their effectiveness in numerous randomized studies, must now be implemented in routine practice. These three different types of optimization devices are caps (enabling exploration of a larger surface area of colonic mucosa), artificial intelligence (AI) that enhances endoscopist vigilance, and image contrast enhancement devices that make a barely visible flat polyp more visible. The combined use of these three highly complementary devices appears optimal. The gradual shift toward routine practice of optimized screening colonoscopy using these devices will undoubtedly lead to an increase in the minimum required ADR, well beyond the currently recommended rate of 25% in the target population for CRC screening. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is omnipresent in our daily lives and generates questions about its future place in medicine, in general, and in hepatology in particular. Numerous articles have been published in recent years on the subject, highlighting the potential role of AI, particularly in radiology for the diagnosis of hepatocellular carcinoma and hepatic dysmorphia, as well as in pathology. The use of AI will probably expand and play an increasingly important role at different stages of patient care: screening for cirrhosis in general medicine, predicting the risk of developing advanced fibrosis or esophageal varices. AI could also help identify the ideal candidate for a liver transplant for cirrhosis linked to an alcohol use disorder and interfere in the doctor-patient relationship by responding in a "more empathetic" way to questions asked by patients. This mini-review presents some applications of AI in our specialty. [ABSTRACT FROM AUTHOR]

In this short response to the papers appearing in this special issue (Technology, AI Bots and Psychotherapy After Covid), psychotherapist and author Aaron Balick draws on the variety of themes that have arisen within the contributed papers to reflect on the wider issue of computer mediated human relations. In it he makes a distinction between the papers that focus on the therapeutic process mediated by technology and those that look more broadly at the paradigm of therapy practice in this context. Framing technology as a tool, the author pulls together both strands to explore what psychotherapy research may say about the broader issues of societies mediated by technology and how therapeutic research may contribute to these larger social issues. [ABSTRACT FROM AUTHOR]

Copyright of European Review of Public Law is the property of European Public Law Organization and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of European Review of Public Law is the property of European Public Law Organization and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of European Review of Public Law is the property of European Public Law Organization and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of European Review of Public Law is the property of European Public Law Organization and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of European Review of Public Law is the property of European Public Law Organization and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of European Review of Public Law is the property of European Public Law Organization and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of European Review of Public Law is the property of European Public Law Organization and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of European Review of Public Law is the property of European Public Law Organization and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Orthodontie Française is the property of John Libbey Eurotext Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Sante Mentale au Quebec is the property of Revue Sante Mentale au Quebec and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Gastrointestinal angiodysplasia are the most common vascular lesions of the digestive tract. Risk factors include age, aortic stenosis (Heyde syndrome), chronic renal failure, cirrhosis and von Willebrandt's disease. Diagnosis is often made in the setting of occult or overt gastrointestinal bleeding. Due to their preferential location in the jejunum and colon, most lesions are diagnosed during upper endoscopy or colonoscopy. In cases where small bowel bleeding is suspected, capsule endoscopy is the gold standard diagnostic exam. A meta-analysis has recently shown that its diagnostic yield is optimal within 48 hours following an overt bleeding episode, and it is recommended to respect this time frame (European Guidelines). Capsule endoscopy is ideal in terms of patient tolerance. However, it is tedious and time-consuming to interpret and requires expertise. In the recent years artificial intelligence applied to capsule endoscopy has developed significantly. Its contribution is now major, with improved diagnostic yield and reduced interpretation time. Argon plasma coagulation during endoscopy is the first-line treatment for gastrointestinal angiodysplasia. Deep enteroscopy is the preferred procedure for ablation of small bowel angiodysplasia. Motorized spiral enteroscopy has enabled easier access to deep small bowel lesions and a shorter procedure time, since it was first used in 2016. However, it has been withdrawn from the market since July 2023, given the occurrence of serious adverse events (perforations). More centres should be equipped with double-ballon enteroscopes in France. The recent results from the randomized controlled OCEAN trial confirm that long-acting release somatostatin analogues (Octreotide) significantly reduce transfusion needs when endoscopic treatment has failed. Thalidomide is also an interesting treatment option, as demonstrated in a randomized control trial published in November 2023, with a reduced recurrence rate of bleeding after 4 months of treatment and during the following year. In the specific case of Heyde syndrome, percutaneous aortic valve replacement (TAVI) also reduces transfusion requirements. [ABSTRACT FROM AUTHOR]

ABSTRACT: Artificial Intelligence (AI) has rapidly expanded across various fields, impacting society by transforming linguistic and cultural habits in translation and breaking down language barriers. While offering opportunities like instant translations and recognition software, caution is necessary due to AI's limitations, particularly in automatic translation. The evolving interaction between humans and machines creates new frontiers in global connectivity, prompting questions about their roles in translation for the humanities and social sciences. Our analysis explores the current state of AI, its possibilities, and tools, focusing on its role in literary and academic translation. We also delve into the limits and risks of AI, underscoring the vital role of the human translator. The central question revolves around whether AI, especially in automatic translation, can reliably serve the humanities. Our hypothesis asserts that the human translator is crucial, using knowledge and experience to provide authentic translations, with the machine acting as a legitimate complement, tempered by the cultural insight of the human translator. RÉSUMÉ : L'intelligence artificielle (IA) s'est rapidement développée dans divers domaines, impactant la société en transformant les habitudes linguistiques et culturelles en matière de traduction et en éliminant les barrières linguistiques. Les possibilités qu’offre cette intelligence pour la traduction sont énormes. Toutefois, il est important de faire attention, car il s’agit enfin de machines programmées à cet effet. Le recours de plus en plus accru à ces machines de traduction qui évoluent rapidement suscite des interrogations des spécialistes de la traduction quant à la fiabilité et l’important domaine recouvert par ces dernières. D’autres questions émanent également sur leur conséquence et la place à occuper face au traducteur humain. C’est pourquoi notre analyse explore l’état actuel de l’IA, ses possibilités, ses outils et son rôle dans la traduction littéraire et académique. Il sera question, conjointement à cela, de voir les limites et les risques de l’IA, en soulignant le rôle vital du traducteur humain. En somme, la question centrale est de savoir si l’IA, en particulier dans la traduction automatique, peut servir de manière fiable les sciences humaines. Notre hypothèse affirme que l’intervention du traducteur humain dans cette équation est primordiale. Ses connaissances et son expérience seraient essentielles pour fournir des traductions authentiques.

ABSTRACT: The central theme in Klara and the Sun is that of Artificial Intelligence. To study it, Julia Kristeva’s semantalysis was useful. The theorist proposes not to be limited to purely textual phenomena so as to be interested in the decryption of analytical categories. Thus, Kazuo Ishiguro under the pivots of pheno-text and geno-text conceptualized his novel as a maieutic of soul of artificial Human. RÉSUMÉ : Le thème central dans Klara et le Soleil est celui de l’Intelligence Artificielle. Pour en faire l’étude, la sémanalyse de Julia Kristeva a été utile. La théoricienne propose de ne pas se limiter aux phénomènes purement textuels de sorte à s’intéresser au plus haut point au décryptage des catégories analytiques. Ainsi, Kazuo Ishiguro sous les pivots du phéno-texte et du géno-texte a conceptualisé son roman comme une maïeutique de l’âme de l’Homme artificiel.

Cet article rend compte d’une recherche-action conduite avec les concepteurs d’une IA émotionnelle qui tentaient de s’éloigner du modèle de capture des technologies affectives. Un tel déplacement implique de rattacher une approche critique et des pratiques d’intervention. Saisir et faire agir forment un couple qui vient compléter une éthique des devoirs ou des conséquences, non plus en aidant les concepteurs à arbitrer entre des principes ou des calculs, mais en leur offrant de repartir de leurs expériences, et celles de leurs usagers, pour concevoir une innovation socialement désirable. Cette promesse est rendue possible par une éthique en situations, un cadrage opérationnel permettant de saisir, par la voie d’une ethnographie sensible, ce qui est à disposition dans les situations vécues par les usagers et par les concepteurs ; de mettre à leur disposition, par des approches participatives, des objets intermédiaires facilitant la transition vers des imaginaires autres ; et de se tenir à disposition pour des médiations nouvelles, en s’appuyant sur des méthodes créatives et projectives.

The article aims to present UNESCO's contribution to generative artificial intelligence (GenAI) in the service of education. To accomplish this, the author first sketches a brief overview of the actions taken by the organization, in particular the most recent publications that demonstrate the commitment to promoting AI in service of education from a humanistic perspective. She then presents a global guide that offers an orientation to GenAI in education and research, followed by its implications for teachers, students, and researchers. [ABSTRACT FROM AUTHOR]

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Copyright of Environnement, Risques & Santé is the property of John Libbey Eurotext Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: This case study investigates how dominant narratives and hegemonic ideals shape technological discourses in explanatory journalism. It examines dominant media frames in articles on technology, artificial intelligence (AI), and robotics in a multinational outlet for explanatory journalism. Analysis: Before and during the first wave of the COVID-19 pandemic, media frames in articles on the aforementioned topics were analyzed to determine their prevalence and impact. Conclusions and implications: Framing robotic and AI-powered technologies shapes the perception of these technologies and of the institutional bodies surrounding them. This research explores connections and considers the initial impact of COVID-19 on the use of media frames and hegemonic narratives. [ABSTRACT FROM AUTHOR]

Les cancers du sein (CS) sont d'une grande hétérogénéité clinique, morphologique et biologique. Même si certaines tumeurs présentent le même phénotype, leurs caractéristiques biologiques et la réponse aux traitements peuvent différer. Les analyses moléculaires à haut débit ont permis de mieux comprendre la biologie de ces cancers et d'identifier des sous-classes moléculaires. La classification morphologique des CS reste primordiale en constante évolution et nous citerons quelques modifications de la nouvelle classification de l'Organisation mondiale de la Santé (OMS) 2019 (cinquième édition) comprenant de nouvelles entités et des mises à jour des critères diagnostiques de certains types tumoraux. Nous verrons également l'entrée de paramètres moléculaires dans la stratification des patientes, des biomarqueurs "anciens" mais qui connaissent un regain d'intérêt comme HER2 et nouvellement introduits dans la pathologie mammaire comme PD-L1, qui sont d'intérêt par leur impact sur la décision thérapeutique. Enfin nous conclurons par un bref aperçu des technologies émergentes dont l'intelligence artificielle pouvant être, dans un futur proche, d'une aide précieuse dans l'évaluation en routine des cancers du sein ou la prédiction du risque de récidive. L'ensemble de ces avancées contribue à la personnalisation de la prise en charge des patientes atteintes d'un CS. Breast cancer (BC) is highly heterogeneous in clinical, morphological and biological terms. Even if certain tumors present the same phenotype, their biological characteristics and response to treatment may differ. High-throughput molecular analyses have enabled us to better understand the biology of these cancers and identify molecular subclasses. Morphological classification of SCs remains paramount in constant evolution, and we will cite some changes in the new 2019 WHO classification (5th edition) including new entities and updates to the diagnostic criteria for certain tumor types. We will also see the introduction of biological parameters in patient stratification, biomarkers that are known but are experiencing renewed interest such as HER2 and newly introduced in breast pathology such as PD-L1, which are of interest for their impact on therapeutic decision. We will conclude with a brief overview of emerging technologies, including artificial intelligence, which could prove invaluable in routine breast cancer assessment or the prediction of the recurrence risk in the near future. All these advances contribute to personalized care for patients with BC. [ABSTRACT FROM AUTHOR]

This article aims to examine the scientific production on the impact on education of technologies related to Artificial Intelligence (AI), between the years 2013 and 2023, to parameterize existing data and provide relevant information to researchers on: scientific publications, the influence they have had, and the frequency with which they have been referenced. This study adopts a descriptive research design and a non-experimental approach in the form of a systematic investigation. The sample consisted of 939 documents. When performing the bibliometric analysis, the co-occurrence of the descriptors allowed the selection of 50 words, generating 6 co-occurrence clusters. Although a total of 2,649 authors were identified in the network of co-authors, only authors who had been cited at least twice were selected. Following this refinement, 63 authors were shortlisted. Finally, we focused our analysis on 15 authors as they were the ones concentrating the largest set of connected elements in the author co-citation network. Following the analysis of the documents, it is concluded that the use of AI in education constitutes an unparalleled opportunity for both education and its stakeholders to adjust to current technological trends. In this context, teachers, students, and families need to update themselves to respond to the challenges posed by available AI tools when it comes to potentiating teaching and learning processes. [ABSTRACT FROM AUTHOR]

L’interview de Stuart Selber réalisée par Jim Ridolfo dans ce numéro spécial intitulé « La rhétorique en-dehors des sentiers battus » donne un aperçu de la carrière innovante et marquante de Selber dans le domaine de la rhétorique numérique. De la monographie primée de Selber, Multiliteracies for a Digital Age, parue en 2004, à sa toute dernière monographie Institutional Literacies : Engaging Academic IT Contexts for Writing and Communication, nous discutons de la manière dont les littératies et les paysages de la rhétorique numérique ont changé de manière significative et continueront à changer alors que nous entrons dans une ère où se multiplient les préoccupations en matière de protection de la vie privée, de deep fakes et d’IA générative. Le travail du professeur Selber est un excellent exemple de la façon dont la recherche en rhétorique numérique contemporaine révolutionne le domaine de la rhétorique traditionnelle et l’enseignement de la littératie, en réélaborant ses notions de base et en élargissant ses applications futures.

Dans un contexte où l’intégration de l’IA dans les processus, produits et services des organisations devient cruciale, nous avons conduit une recherche centrée sur le développement des compétences en gestion de projets d’IA et avons constaté l’importance croissante des compétences transversales (soft skills). L’objectif était de saisir les dimensions collaboratives versus les dimensions individuelles dans l’acquisition de ces compétences, traditionnellement acquises dans un environnement collectif de travail, du point de vue des gestionnaires de projets IA. Notre texte traite du processus de développement d’un référentiel de compétences, coconstruit avec les experts du domaine, ainsi que des analyses dégagées de ce processus sur le plan des compétences requises et du mode d’acquisition de ces compétences pour le développement de l’identité professionnelle. Ce référentiel vise à orienter les stratégies de formation en gestion de l’IA des établissements de formation, afin qu’ils puissent concevoir des formations adaptées à la réalité du milieu du travail, incluant des besoins d’apprentissage collaboratif.

Nous constatons la convergence de deux problématiques : les très grands écarts de compétences numériques des étudiants qui entrent à l’université et la montée du numérique, ici représenté par les intelligences artificielles. Cette convergence rend la situation de moins en moins tenable dans les universités en imposant une pression de plus en plus importante sur les professeurs, les chargés de cours et les professionnels qui les accompagnent. Nous proposons que cette situation puisse être potentiellement corrigée ou améliorée en révisant la place de la compétence numérique au sein du programme de formation québécois.

Cet article présente une recension des écrits sur la façon dont les rôles de l’enseignant et de l’intelligence artificielle (IA) sont abordés dans le domaine de l’intelligence artificielle en éducation (IAED) depuis 1970. Quarante-sept documents, théoriques pour la plupart, ont été analysés à partir des passages relatifs aux tâches confiées à une IA en lien avec les apprenants, les enseignants, les savoirs ou la classe (p. ex. le soutien à la motivation ou la rétroaction personnalisée). Les passages qui discutent du rôle de l’enseignant en lien avec ces différentes composantes ont aussi été analysés (p. ex. le pilotage des interactions en classe ou l’évaluation des apprenants). Les principaux résultats montrent que les développements dans le domaine de l’IAED couvrent un large spectre des attributions de l’enseignant et que, même si inatteignable sur un horizon prévisible, l’ambition scientifique du domaine semble être d’automatiser de plus en plus de tâches de l’enseignant. Il en ressort que le rôle de l’enseignant est très peu discuté dans le domaine, et encore moins les interactions attendues entre enseignants et IA. La discussion propose de réemployer le tétraèdre des TIC en éducation de Faerber (2003), lui-même appuyé sur le triangle didactique de Houssaye (1988), pour conceptualiser le rôle de l’IA en éducation en interaction avec ceux de l’enseignant et de l’apprenant.

An editorial is presented that delves into the ethical considerations surrounding the development and application of artificial intelligence in healthcare, drawing parallels to science fiction narratives like Isaac Asimov's works. It highlights the rapid advancement of AI technologies in medical diagnostics and conversational AI tools like ChatGPT and Bard, emphasizing the need for robust ethical frameworks to guide their use.