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This study evaluates the quality of published research using artificial intelligence (AI) for ovarian cancer diagnosis or prognosis using histopathology data. A systematic search of PubMed, Scopus, Web of Science, Cochrane CENTRAL, and WHO-ICTRP was conducted up to May 19, 2023. Inclusion criteria required that AI was used for prognostic or diagnostic inferences in human ovarian cancer histopathology images. Risk of bias was assessed using PROBAST. Information about each model was tabulated and summary statistics were reported. The study was registered on PROSPERO (CRD42022334730) and PRISMA 2020 reporting guidelines were followed. Searches identified 1573 records, of which 45 were eligible for inclusion. These studies contained 80 models of interest, including 37 diagnostic models, 22 prognostic models, and 21 other diagnostically relevant models. Common tasks included treatment response prediction (11/80), malignancy status classification (10/80), stain quantification (9/80), and histological subtyping (7/80). Models were developed using 1–1375 histopathology slides from 1–776 ovarian cancer patients. A high or unclear risk of bias was found in all studies, most frequently due to limited analysis and incomplete reporting regarding participant recruitment. Limited research has been conducted on the application of AI to histopathology images for diagnostic or prognostic purposes in ovarian cancer, and none of the models have been demonstrated to be ready for real-world implementation. Key aspects to accelerate clinical translation include transparent and comprehensive reporting of data provenance and modelling approaches, and improved quantitative evaluation using cross-validation and external validations. This work was funded by the Engineering and Physical Sciences Research Council. [ABSTRACT FROM AUTHOR]

Clinical trials of oncolytic virotherapy have shown low toxicity and encouraging signs of efficacy. However, it remains critically important to develop methods for systemic viral delivery if such therapies are to be clinically implemented to treat established tumors. In this respect, much effort is being focused on combining oncolytic viruses with standard treatment modalities such as inhibitors of [VEGF.sub.165] (an alternatively spliced isoform of VEGF-A) signaling, which are widely used to treat several different cancers. Here, we have demonstrated that combining [VEGF.sub.165] inhibitors with systemic delivery of oncolytic viruses leads to substantial regression and cure of established tumors in immunocompetent mice. We have shown that manipulating VEGF165-mediated signaling by administering [VEGF.sub.165] to mice harboring mouse melanoma cells that do not express [VEGF.sub.165]and by administering a VEGF inhibitor and then withdrawing treatment to allow VEGF levels to rebound in mice harboring mouse melanoma cells expressing [VEGF.sub.165] allows tumor-associated endothelial cells transiently to support viral replication. This approach led to direct tumor cell lysis and triggered innate immune-mediated attack on the tumor vasculature. It also resulted in long-term antitumor effects, even against tumors in which viral replication is poorly supported. Since this combinatorial approach targets the tumor endothelium, we believe these data have direct, wide-ranging, and immediate clinical applicability across a broad range of tumor types., Introduction Cancer gene/virus therapy will not achieve its potential until vectors can be delivered systemically to metastatic disease (1). Many barriers exist in immunocompetent hosts, including immune inactivation, mislocalization, specific [...]

I-ImaS (Intelligent Imaging Sensors) is a European project aiming to produce new, intelligent x-ray imaging systems using novel APS sensors to create optimal diagnostic images. Initial systems have been constructed for medical imaging; specifically mammography and dental encephalography. However, the I-ImaS system concept could be applied to all areas of x-ray imaging, including homeland security and industrial QA. The I-ImaS system intelligence is implemented by the use of APS technology and FPGAs, allowing real-time analysis of data during image acquisition. This gives the system the capability to perform as an on-the-fly adaptive imaging system, with the potential to create images with maximum diagnostic information within given dose constraints. The I-ImaS system uses a scanning linear array of scintillator-coupled 1.5-D CMOS Active Pixel Sensors to create a full 2-D x-ray image of an object. This paper describes the parameters considered when choosing the scintillator elements of the detectors. A study of the positioning of the sensors to form a linear detector is also considered, along with a discussion of the potential losses in image quality associated with creating a linear sensor by tiling many smaller sensors. Preliminary results show that the detectors have sufficient performance to be used successfully in the initial mammographic and encephalographic I-ImaS systems that are currently under construction. Index Terms--CMOS, scintillators, x-ray imaging.

Radiation hardness is a critical design concern for present and future silicon detectors in high energy physics. Tracking systems at the CERN Large Hadron Collider (LHC) are expected to operate for ten years and to receive fast hadron fluences equivalent to [10.sup.15][cm.sup.2] 1-MeV neutrons. Recently, low temperature operating conditions have been suggested as a means of suppressing the negative effects of radiation damage on detector charge collection properties. To investigate this effect, simulations have been carried out using the ISE-TCAD DESSIS device simulator. The so-called 'three-level model' has been used. A comprehensive analysis of the influence of the [V.sub.2], [C.sub.i][O.sub.i] and [V.sub.2]O capture cross sections on the effective doping concentration ([N.sub.eff]) as a function of temperature and fluence has been carried out. The capture cross sections have been varied in the range [10.sup.-18] - [10.sup.-12] [cm.sup.2]. The simulated results are compared with charge collection spectra obtained with 1064-nm laser pulses on devices irradiated with 23-GeV protons as a function of detector bias voltage. To validate the model, a wide range of temperature and fluence has been studied using a one-dimensional (1-D) simplified structure. Thousands of simulation results have been cross checked with the experimental data. The data between 190 K (the lower limit for simulations due to computational difficulties) and 290 K are well reproduced for all of the fluences considered. We conclude that the three-level model can be successfully used to predict irradiated detector behavior down to a temperature of at least 190 K. Index Terms--Cryogenic temperatures, device simulation, particle physics, radiation damage effects.

The effect of particle irradiation on high-resistivity silicon detectors has been extensively studied with the goal of engineering devices able to survive the very challenging radiation environment at the CERN Large Hadron Collider (LHC). The main aspect under investigation has been the changes observed in detector effective doping concentration ([N.sub.eff]). We have previously proposed a mechanism to explain the evolution of [N.sub.eff], whereby charge is exchanged directly between closely-spaced defect centres in the dense terminal clusters formed by hadron irradiation. This model has been implemented in both a commercial finite-element device simulator (ISE-TCAD) and a purpose-built simulation of interdefect charge exchange. To control the risk of breakdown due to the high leakage currents foreseen during ten years of LHC operation, silicon detectors will be operated below room temperature (around -10[degrees]C. This, and more general current interest in the field of cryogenic operation, has led us to investigate the behavior of our model over a wide range of temperatures. We present charge collection spectra from 1064 nm laser pulses as a function of detector bias between temperatures of 115 K and 290 K, using devices irradiated with 23 GeV protons in the range [10.sup.13] -4 x [10.sup.14] protons * [cm.sup.-2]. These data allow a deeper investigation of the influence of defect capture cross sections on [N.sub.eff]. The model prediction for the reversion to n-type of heavily-irradiated detectors at low temperature is investigated and deviations from the model are explored. Index Terms--Cryogenic operation, particle physics, radiaiton effects, silicon radiation detectors.

New guidance issued by the National Institute for Clinical Excellence (NICE) is set to cut dramatically the number of hospital admissions resulting from head injury and improve patient care. It [...]

Introduction: More people are living with and beyond a cancer diagnosis. There is limited understanding of the long-term effects of cancer and cancer treatment on quality of life and personal and household finances when compared to people without cancer. In a separate protocol we have proposed to link de-identified data from electronic primary care and hospital records for a large population of cancer survivors and matched controls. In this current protocol, we propose the linkage of Patient Reported Outcomes Measures data to the above data for a subset of this population. The aim of this study is to investigate the full impact of living with and beyond a cancer diagnosis compared to age and gender matched controls. A secondary aim is to test the feasibility of the collection of Patient Reported Outcomes Measures (PROMS) data and the linkage procedures of the PROMs data to electronic health records data. Materials and methods: This is a cross-sectional study, aiming to recruit participants treated at the Leeds Teaching Hospitals National Health Service Trust. Eligible patients will be cancer survivors at around 5 years post-diagnosis (breast, colorectal and ovarian cancer) and non-cancer patient matched controls attending dermatology out-patient clinics. They will be identified by running a query on the Leeds Teaching Hospitals Trust patient records system. Approximately 6000 patients (2000 cases and 4000 controls) will be invited to participate via post. Participants will be invited to complete PROMs assessing factors such as quality of life and finances, which can be completed on paper or online (surveys includes established instruments, and bespoke instruments (demographics, financial costs). This PROMs data will then be linked to routinely collected de-identified data from patient's electronic primary care and hospital records. Discussion: This innovative work aims to create a truly 'comprehensive patient record' to provide a broad picture of what happens to cancer patients across their cancer pathway, and the long-term impact of cancer treatment. Comparisons can be made between the cases and controls, to identify the aspects of life that has had the greatest impact following a cancer diagnosis. The feasibility of linking PROMs data to electronic health records can also be assessed. This work can inform future support offered to people living with and beyond a cancer diagnosis, clinical practice, and future research methodologies. [ABSTRACT FROM AUTHOR]

Silicon particle detectors in the next generation of experiments at the CERN Large Hadron Collider will be exposed to a very challenging radiation environment. The principal obstacle to long-term operation arises from changes in detector doping concentration ([N.sub.eff]), which lead to an increase in the bias required to deplete the detector and hence achieve efficient charge collection. We have previously presented a model of interdefect charge exchange between closely spaced centers in the dense terminal clusters formed by hadron irradiation. This manifestly non-Shockley-Read-Hall (SRH) mechanism leads to a marked increase in carrier generation rate and negative space charge over the SRH prediction. There is currently much interest in the subject of cryogenic detector operation as a means of improving radiation hardness. Our motivation, however, is primarily to investigate our model further by testing its predictions over a range of temperatures. We present here measurements of spectra from [sup.241]Am alpha particles and 1064-nm laser pulses as a function of bias between 120 and 290 K. Values of [N.sub.eff] and substrate type are extracted from the spectra and compared with the model. The model is implemented in both a commercial finite-element device simulator (ISE-TCAD) and a purpose-built simulation of interdefect charge exchange. Deviations from the model are explored and comments made as to possible future directions for investigation of this difficult problem. Index Terms--Position sensitive particle detectors, semiconductor defects, semiconductor device radiation effects, silicon, temperature.

Since the emergence of COVID-19, deep learning models have been developed to identify COVID-19 from chest X-rays. With little to no direct access to hospital data, the AI community relies heavily on public data comprising numerous data sources. Model performance results have been exceptional when training and testing on open-source data, surpassing the reported capabilities of AI in pneumonia-detection prior to the COVID-19 outbreak. In this study impactful models are trained on a widely used open-source data and tested on an external test set and a hospital dataset, for the task of classifying chest X-rays into one of three classes: COVID-19, non-COVID pneumonia and no-pneumonia. Classification performance of the models investigated is evaluated through ROC curves, confusion matrices and standard classification metrics. Explainability modules are implemented to explore the image features most important to classification. Data analysis and model evalutions show that the popular open-source dataset COVIDx is not representative of the real clinical problem and that results from testing on this are inflated. Dependence on open-source data can leave models vulnerable to bias and confounding variables, requiring careful analysis to develop clinically useful/viable AI tools for COVID-19 detection in chest X-rays. [ABSTRACT FROM AUTHOR]

Most data collected by hospitals as a consequence of the delivery of routine care is not utilised for analytics or organisational intelligence. This project aims to develop tools to enhance the utilisation of routinely collected cancer data within hospitals across England. This was achieved by developing a web application using open source tools to provide health care professionals and hospital managers with easy to use, interactive analytics for cancer data. The application uses data items hospitals in England are mandated to collect as part of the Cancer Outcomes and Services Dataset (COSD), to provide clinical insight into survival outcomes, population distributions, service demands, waiting times, geographical case distributions and treatment information in real-time or near real-time. Development was guided by end user needs through the use of panels of clinical and non-clinical end users. [ABSTRACT FROM AUTHOR]

Background: The use of linked healthcare data in research has the potential to make major contributions to knowledge generation and service improvement. However, using healthcare data for secondary purposes raises legal and ethical concerns relating to confidentiality, privacy and data protection rights. Using a linkage and anonymisation approach that processes data lawfully and in line with ethical best practice to create an anonymous (non-personal) dataset can address these concerns, yet there is no set approach for defining all of the steps involved in such data flow end-to-end. We aimed to define such an approach with clear steps for dataset creation, and to describe its utilisation in a case study linking healthcare data. Methods: We developed a data flow protocol that generates pseudonymous datasets that can be reversibly linked, or irreversibly linked to form an anonymous research dataset. It was designed and implemented by the Comprehensive Patient Records (CPR) study in Leeds, UK. Results: We defined a clear approach that received ethico-legal approval for use in creating an anonymous research dataset. Our approach used individual-level linkage through a mechanism that is not computer-intensive and was rendered irreversible to both data providers and processors. We successfully applied it in the CPR study to hospital and general practice and community electronic health record data from two providers, along with patient reported outcomes, for 365,193 patients. The resultant anonymous research dataset is available via DATA-CAN, the Health Data Research Hub for Cancer in the UK. Conclusions: Through ethical, legal and academic review, we believe that we contribute a defined approach that represents a framework that exceeds current minimum standards for effective pseudonymisation and anonymisation. This paper describes our methods and provides supporting information to facilitate the use of this approach in research. [ABSTRACT FROM AUTHOR]

An environmentalism scale of known internal consistency and scales of three different types of conservatism were completed by a community sample of 299 shoppers in Brisbane, Australia, to measure the relationship between environmentalism and conservatism. Environmentalism and conservatism were found to be essentially unrelated., Research on the radicalism and conservatism of environmentalists has shown that a priori considerations are not helpful (Wells, 1978). On the one hand, environmentalists clearly want to conserve many things [...]

The main challenge in the pathway analysis of cancer treatments is the complexity of the process. Process mining is one of the approaches that can be used to visualize and analyze these complex pathways. In this study, our purpose was to use process mining to explore variations in the treatment pathways of endometrial cancer. We extracted patient data from a hospital information system, created the process model, and analyzed the variations of the 62-day pathway from a General Practitioner referral to the first treatment in the hospital. We also analyzed the variations based on three different criteria: the type of the first treatment, the age at diagnosis, and the year of diagnosis. This approach should be of interest to others dealing with complex medical and healthcare processes. [ABSTRACT FROM AUTHOR]

The article presents the discussion on history of EMWA (1992-2008). Topics include telling a tale of flirtation, marriage, divorce, remarriage, betrayal and separation which being just the relationship between EMWA and the American cousin, the American Medical Writers Association (AMWA); and contributing to speakers' and workshop leaders' expenses as well as providing free use of the company's first class conference facilities.

Objectives: To characterize treatment patterns and survival outcomes for patients with locally advanced or metastatic malignancy of the urothelial tract during a period immediately preceding the widespread use of immune checkpoint inhibitors in the UK. Patients and Methods: We retrospectively examined the electronic case notes of patients attending the Leeds Cancer Center, UK with locally advanced or metastatic urothelial carcinoma, receiving chemotherapy between January 2003 and March 2017. Patient characteristics, treatment patterns, and outcomes were collected. Summary and descriptive statistics were calculated for categorical and continuous variables as appropriate. The Kaplan–Meier method was used to estimate median survival and Cox regression proportional hazards model was used to explore relationships between clinical variables and outcome. Results: Two hundred and sixteen patients made up the study cohort, with a median age of 66 years (range: 35–83) and 72.7% being male. First-line treatment consisted of either a cisplatin- (44%) or carboplatin-based regimen (48%) in the majority of patients. Twenty seven percent of patients received a second-line of treatment (most commonly single-agent paclitaxel) following a first-line platinum containing regimen. Grade 4 neutropenia was observed in 19 and 27% of those treated with a first-line cisplatin- and carboplatin-based regimen, respectively. The median overall survival (mOS) of the study cohort was estimated to be 16.2 months (IQR: 10.6–28.3 months). Receipt by patients of cisplatin-based chemotherapy was associated with a longer mOS and this association persisted when survival analysis was adjusted for age, sex, performance status and presence of distant metastases. Conclusions: This study provides a useful benchmark for outcomes achieved in a real-world setting for patients with locally advanced or metastatic UC treated with chemotherapy in the immediate pre-immunotherapy era. [ABSTRACT FROM AUTHOR]

Background: The 2-week-wait urgent referral policy in the UK has sought to improve cancer outcomes by accelerating diagnosis and treatment. However, around 5–7% of symptomatic referred patients cancel or do not attend their hospital appointment. While subsequent cancer diagnosis was less likely in non-attenders, those with a diagnosis had worse early mortality outcomes. Aim: To examine how interpersonal, communication, social, and organisational factors influence a patient's non-attendance. Design and setting: Qualitative study in GP practices in one Northern English city. Method: In-depth, individual interviews were undertaken face-to-face or by telephone between December 2016 and May 2018, followed by thematic framework analysis. Results: In this study 21 GPs, and 24 patients who did not attend or had cancelled their appointment were interviewed, deriving a range of potential explanations for non-attendance, including: system flaws; GP difficulties with booking appointments; patient difficulties with navigating the appointment system, particularly older patients and those from more deprived areas; patients leading 'difficult lives'; and patients' expectations of the referral, informed by their beliefs, circumstances, priorities, and the perceived prognosis. GPs recognised the importance of communication with the patient, particularly the need to tailor communication to perceived patient understanding and anxiety. GPs and practices varied in their responses to patient non-attendance, influenced by time pressures and perceptions of patient responsibility. Conclusion: Failure to be seen within 2 weeks of urgent referral resulted from a number of patient and provider factors. The urgent referral process in general practice and cancer services should accommodate patient perceptions and responses, facilitate referral and attendance, and enable responses to patient non-attendance. [ABSTRACT FROM AUTHOR]

There is a growing body of literature on process mining in healthcare. Process mining of electronic health record systems could give benefit into better understanding of the actual processes happened in the patient treatment, from the event log of the hospital information system. Researchers report issues of data access approval, anonymisation constraints, and data quality. One solution to progress methodology development is to use a high-quality, freely available research dataset such as Medical Information Mart for Intensive Care III, a critical care database which contains the records of 46,520 intensive care unit patients over 12 years. Our article aims to (1) explore data quality issues for healthcare process mining using Medical Information Mart for Intensive Care III, (2) provide a structured assessment of Medical Information Mart for Intensive Care III data quality and challenge for process mining, and (3) provide a worked example of cancer treatment as a case study of process mining using Medical Information Mart for Intensive Care III to illustrate an approach and solution to data quality challenges. The electronic health record software was upgraded partway through the period over which data was collected and we use this event to explore the link between electronic health record system design and resulting process models. [ABSTRACT FROM AUTHOR]

Background: Equations to estimate glomerular filtration rate based on serum creatinine are commonly used in cancer patients to assess renal function. However, there is uncertainty regarding which equation is most appropriate for this population and the impact of different creatinine assays.Methods: Measured isotopic glomerular filtration rate results from 120 oncology patients were used to evaluate and compare all four versions of the Wright equation, Cockcroft and Gault, Modification of Diet in Renal Disease (MDRD), Chronic Kidney Disease Epidemiology Collaboration and the Janowitz and Williams formula; using eight different creatinine assays (five Jaffe, three enzymatic).Results: The enzymatic version of the Wright equation without creatine kinase performed better than the other versions for all eight creatinine assays. However, MDRD and Janowitz and Williams gave the best overall performance in this patient population. Performance was highly dependent on the creatinine assay used, for example, the percentage of results within 30% of the isotopic glomerular filtration rate (P30) ranged from 90.8% to 60.8% for MDRD.Conclusion: The performance of any equation to estimate glomerular filtration rate is highly dependent on the creatinine assay used. Oncology units should assess the performance of glomerular filtration rate equations using their laboratory creatinine assay to determine whether they can be used safely and effectively in cancer patients. [ABSTRACT FROM AUTHOR]