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The increasing digitization of the healthcare system is leading to a growing volume of health data. Leveraging this data beyond its initial collection purpose for secondary use can provide valuable insights into diagnostics, treatment processes, and the quality of care. The Health Data Lab (HDL) will provide infrastructure for this purpose. Both the protection of patient privacy and optimal analytical capabilities are of central importance in this context, and artificial intelligence (AI) provides two opportunities. First, it enables the analysis of large volumes of data with flexible models, which means that hidden correlations and patterns can be discovered. Second, synthetic - that is, artificial - data generated by AI can protect privacy.This paper describes the KI-FDZ project, which aims to investigate innovative technologies that can support the secure provision of health data for secondary research purposes. A multi-layered approach is investigated in which data-level measures can be combined in different ways with processing in secure environments. To this end, anonymization and synthetization methods, among others, are evaluated based on two concrete application examples. Moreover, it is examined how the creation of machine learning pipelines and the execution of AI algorithms can be supported in secure processing environments. Preliminary results indicate that this approach can achieve a high level of protection while maintaining data validity. The approach investigated in the project can be an important building block in the secure secondary use of health data., (© 2024. The Author(s).)

Big data and artificial intelligence are buzzwords that everyone is talking about and yet always provide a touch of science fiction to the scenery. What is the status of these topics in anesthesia? Are the first robots already rolling through the corridors while doctors are getting bored as all the work has been done? Spoiler alert! We are still far away from achieving this. Initially, paper charts and analogue notes stand in the way of comprehensive digitization. Source systems need to be merged and data standardized, harmonized and validated. Therefore, the friendly android that is rolling towards us, waving and holding a freshly brewed cup of coffee in our thoughts will have to wait; however, a glimpse of the future is already evident in some clinics and the first promising developments are already showing what could be the standard tomorrow. Learning algorithms calculate the length of stay individually for each patient in the intensive care unit (ICU), reducing negative consequences such as readmission and mortality. The field of ultrasound technology for regional anesthesia and closed-loop anesthesia systems is also demonstrating the benefits of artificial intelligence (AI)-assisted technologies in practice. The efforts are diverse and ambitious but they repeatedly collide with privacy challenges and significant capital expenditure, which weigh heavily on an already financially strained healthcare system; however, anyone who listens carefully to the medical staff knows that robots are not what they would expect and the buzzwords big data and artificial intelligence might be less science fiction than initially assumed. [ABSTRACT FROM AUTHOR]

Copyright of Sozialer Fortschritt is the property of Duncker & Humblot GmbH 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.)

In this paper methods and algorithms are examined for solving one important problem of transport logistics, namely formation of roadmap. The proposed mathematical model is based on the well-known multi-depot heterogeneous vehicle routing problem with time windows algorithm. Modifications of the model provide additional conditions and restrictions. Algorithmic support of information transport system in an enterprise is connected with features of the vehicle routing problem. The suggested solution is based on modified Clarke and Wright Algorithm and Variable Neighborhood Search. The risk on the roads and the cost of toll roads are calculated, too. [ABSTRACT FROM AUTHOR]

Copyright of Der Gynäkologe is the property of Springer Nature 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 Österreichische Zeitschrift für Soziologie is the property of Springer Nature 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 Automatisierungstechnik is the property of De Gruyter 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: Low back pain is a common problem for primary care providers, outpatient clinics and A&E departments. The predominant symptoms are those of so-called "unspecific back pain", but serious pathologies can be concealed by the clinical signs. Especially less experienced colleagues have problems in treating these patients, as - despite the multitude of recommendations and guidelines - there is no generally accepted algorithm., Methods: After a literature search (Medline/Cochrane), 158 articles were selected from 15,000 papers and classified according to their level of evidence. These were attuned to the clinical guidelines of the orthopaedic and pain-physician associations in Europe, North America and overseas and the experience of specialists at LMU Munich, in order to achieve consistency with literature recommendations, as well as feasibility in everyday clinical work and optimised with practical relevance., Results: An algorithm was formed to provide the crucial differential diagnosis of lumbar back pain according to its clinical relevance and to provide a plan of action offering reasonable diagnostic and therapeutic steps. As a consequence of distinct binary decisions, low back patients should be treated at any given time according to the guidelines, with emergencies detected, unnecessary diagnostic testing and interventions averted and reasonable treatment initiated pursuant to the underlying pathology., Conclusion: In the context of the available evidence, a clinical algorithm has been developed that translates the complex diagnostic testing of acute low back pain into a transparent, structured and systematic guideline., Competing Interests: Die Autoren geben an, dass kein Interessenkonflikt besteht., (Georg Thieme Verlag KG Stuttgart · New York.)

This paper is a practical survey of immune-mediated, inflammatory and hereditary neuropathies along with recommendations for diagnostic procedures. The large group of immune-mediated, inflammatory neuropathies includes the Guillain-Barré syndrome and chronic-inflammatory demyelinating polyradiculoneuropathy and their subtypes, vasculitic, paraneoplastic and paraproteinemic neuropathies as well as neuropathies resulting from connective tissue disorders. Besides clinical features such as time-dependent progression and distribution of sensorimotor deficits, characteristic electroneurographic findings and antibody profiles are considered. Recent studies in hereditary neuropathies reveal a prevalence of 10-28 out of 100 000 persons in Europe. Research into the genetic causes has made significant progress in the last 20 years; up to now more than 80 genes mutated in hereditary neuropathies have been identified. Besides classification into axonal, demyelinating or intermediate neuropathies based on electroneurography, distinguishing between sensorimotor, pure motor and (autonomous) sensory neuropathies as well as consideration of particular clinical features and ethnic origin can be helpful in orientating molecular genetic analysis., Competing Interests: Es liegen keine Interessenkonflikte der beiden Autoren vor., (© Georg Thieme Verlag KG Stuttgart · New York.)

Copyright of Briefe zur Interdisziplinarität is the property of Oekom Verlag GmbH 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.)

Artificial Intelligence (AI) has been become a household expression, especially in the past couple of years thanks to Google's AI Computer program AlphaGo defeating a couple of world-class Go masters from Korea and China. In recent years, machines have surpassed humans in the performance of certain specific tasks, such as some aspects of image recognition. Although it is unlikely that machines will exhibit broadly-applicable intelligence comparable to or exceeding that of humans in the near future, experts forecast that rapid progress in the field of specialized AI will continue, with machines reaching and exceeding human performance on an increasing number of tasks. Simultaneous interpreting, being among the most complex of human cognitive/linguistic activities, with all the associated ergonomic elements, has been discussed profusely as one of the most likely to be taken over by AI in a couple of years. Given that so much has to be there simultaneously, i. e. anticipation, restoration of the implicit-explicit balance, and communicative re-packaging ('re-ostension'1) of the discourse, simultaneous interpreting (SI) has yet to be fully explained, not the least the rich pragmatic information guiding the construction of the appropriate contexts and the speaker's underlying intentionalities, which is the centre piece of SI, given the illusive nature of meaning assembly could be quite beyond even the most intelligent robots. This paper discusses what SI is like, how AI has evolved, and concludes that AI is dramatically changing the profession, but given the rulebased nature of AI driven by data and algorithms, human intelligence as possessed by SI practitioners is still irreplaceable. SI practitioners can harness cutting-edge technologies such as AI to do a better job, which bears significance for trainers and would be SIs. [ABSTRACT FROM AUTHOR]

In ionization chambers, not all released charge is collected due to the recombination of charge carriers. This effect is taken into account by the saturation correction factor kS. A physical description of the correction factor has been established for pulsed radiation. However, it is only accurate when the pulse length is short compared with the collection time of the ionization chamber. In this paper we develop a description of the saturation correction for radiation pulses of arbitrary length. For this, a system of partial differential equations is solved iteratively. The numerical solutions are verified experimentally for a Roos ionization chamber (PTW TM34001) exposed to a pulsed electron beam. The results of this iterative procedure describe the experimental data well. The calculations are also possible for beam structures which are experimentally hard to get and thereby contribute to a better understanding and correct description of the saturation correction at arbitrary pulse length. Among other things the pulse length dependent distributions of the charge carriers in the ionization chamber is calculated, inclusive of the transition to the conditions prevailing in the case of continuous irradiation. Furthermore is shown that the formula for kS established by Hochhäuser and Balk is applicable even at arbitrary pulse length, if pulse duration dependent effective values are used for the parameters a and p. These effective values have been determined for the Roos chamber at pulse lengths up to 300 μs., (Copyright © 2013. Published by Elsevier GmbH.)

Clearance monitor systems are used for gross gamma measurements of waste potentially contaminated with radioactivity. These measurements are to make sure that legal requirements, e.g. clearance criteria according to the german radiation protection ordinance, are met. This means that measurement results may overestimate, but must not underestimate the true values. This paper describes a pragmatic way using a calibrated Cs-137 point source to generate a conservative calibration for the clearance monitor system used in the Medizinische Hochschule Hannover (MHH). The most important nuclides used in nuclear medicine are considered. The measurement result reliably overestimates the true value of the activity present in the waste. The calibration is compliant with the demands for conservativity and traceability to national standards., (Copyright © 2014. Published by Elsevier GmbH.)

Algorithms have become an indispensable part of everyday business life. They not only screen markets within a very short time, but also influence the market behavior of companies. In the age of ChatGPT and “deep learning algorithms”, many intriguing questions arise: Can algorithms be “cartel promoters”, “cartel facilitators” or even “cartel initiators”? Is the antitrust concept of “concurrence of wills” still up-to-date? When can the “conduct” of algorithms be attributed to a company? This practice-oriented article is intended to shed light on problematic constellations on the basis of a number of cases. [ABSTRACT FROM AUTHOR]

Copyright of GENDER: Zeitschrift für Geschlecht, Kultur und Gesellschaft is the property of Verlag Barbara Budrich GmbH 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 Geomechanik und Tunnelbau is the property of Wiley-Blackwell 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 article presents August issue of the periodical on the topics of German mathematics education and mathematicians association. Topics include figures and evaluations relating to mathematics studies for Women in Mathematics; and using algorithms in proving mathematical theorems on the progress of mathematics in research and applied mathematician.

The rapidly growing academic and public attention to algorithmic-selection applications such as search engines and social media is indicative of their alleged great social relevance and impact on daily life in digital societies. To substantiate these claims, this paper investigates the hitherto little explored subjective relevance that Internet users assign to algorithmic-selection applications in everyday life. A representative online survey of Internet users comparatively reveals the relevance that users ascribe to algorithmic-selection applications and to their online and offline alternatives in five selected life domains: political and social orientation, entertainment, commercial transactions, socializing and health. The results show that people assign a relatively low relevance to algorithmic-selection applications compared to offline alternatives across the five life domains. The findings vary greatly by age and education. Altogether, such outcomes complement and qualify assessments of the social impact of algorithms that are primarily and often solely based on usage data and theoretical considerations.