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Importance: US law generally requires testing of high-risk medical devices prior to approval, as well as premarket evaluation of moderate-risk medical devices, with the goal of ensuring that the benefits of these products exceed their risks. The US Food and Drug Administration (FDA) attempts to balance the need for evidence generation with an approval process that facilitates access and encourages innovation. Objective: To review the development of laws and standards affecting the evaluation and oversight of medical devices by the US regulatory system and the outcomes of this system from 1976 to 2020. Evidence Review: Laws enacted by US Congress and regulations promulgated by the FDA through 2020; databases maintained by the FDA of device authorizations from 1976 to 2020; and annual reports of user fees paid to the FDA by industry. Findings: Since Congress and the FDA initiated premarket review of medical devices in 1976, some fundamental innovations in the device regulation system have included special pathways to accelerate availability of investigational devices, more flexible evidence and review requirements, and increased funding to the FDA through industry-paid user fees. From 1987 to 2020, the annual number of novel devices granted premarket approval (which excludes supplements) ranged from 8 to 56 (median, 32), and the number of clearances for 510(k) devices (those that are "substantially equivalent" to marketed devices) ranged from 2804 to 5762 (median, 3404). User fee funding for devices was established in 2002 and annual fees collected increased from $30 million in 2003 (in 2019 dollars) to more than $208 million in 2019; this represented 43% of FDA funding related to the review of medical devices. Although many new devices have led to considerable patient benefit, such as hypodermic needles and magnetic resonance imaging machines, important adverse events caused by some devices, such as an implanted device for birth control and a surgical mesh implant for pelvic organ prolapse, have led to calls to reexamine the regulatory system for such products. Conclusions and Relevance: Over the last 45 years, medical device regulation has become more complex, with more regulatory pathways and greater variations in the evidence and controls required for authorization. Increased FDA support from industry and concern about flexible authorization requirements reflect the tension between efficient access and the need for assurances that products will safely benefit patients.

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For more than a decade, we have witnessed an acceleration in the development and the adoption of artificial intelligence (AI) technologies. In medicine, it impacts clinical and fundamental research, hospital practices, medical examinations, hospital care or logistics. These in turn contribute to improvements in diagnostics and prognostics, and to improvements in personalised and targeted medicine, advanced observation and analysis technologies, or surgery and other assistance robots. Many challenges in AI and medicine, such as data digitalisation, medical data privacy, algorithm explicability, inclusive AI system development or their reproducibility, have to be tackled in order to build the confidence of medical practitioners in these technologies. This will be possible by mastering the key concepts via a brief history of artificial intelligence.

TITLE: Une brève introduction à l'intelligence artificielle. ABSTRACT: Depuis plus d'une décennie, l'intelligence artificielle (IA) vit une accélération dans son développement et son adoption. En médecine, elle intervient dans la recherche fondamentale et clinique, la pratique hospitalière, les examens médicaux, les soins ou encore la logistique. Ce qui contribue à l'affinement des diagnostics et des pronostics, à une médecine encore plus personnalisée et ciblée, à des avancées dans les technologies d'observations et d'analyses ou encore dans les outils d'interventions chirurgicales et autres robots d'assistance. De nombreux enjeux propres à l'IA et à la médecine, tels que la dématérialisation des données, le respect de la vie privée, l'explicabilité1 des algorithmes, la conception de systèmes d'IA inclusifs ou leur reproductibilité, sont à surmonter pour construire une confiance du corps hospitalier dans ces outils. Cela passe par une maîtrise des concepts fondamentaux que nous présentons ici.

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The PSIPRED Workbench is a web server offering a range of predictive methods to the bioscience community for 20 years. Here, we present the work we have completed to update the PSIPRED Protein Analysis Workbench and make it ready for the next 20 years. The main focus of our recent website upgrade work has been the acceleration of analyses in the face of increasing protein sequence database size. We additionally discuss any new software, the new hardware infrastructure, our webservices and web site. Lastly we survey updates to some of the key predictive algorithms available through our website.

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El empleo del software educativo ha constituido una exigencia en las transformaciones que en la Educación Médica Superior (EMS) en Cuba han tenido lugar para perfeccionar el Proceso de Enseñanza Aprendizaje (PEA). Al respecto el trabajo expone las características más sobresalientes de las tres etapas por las que ha transitado su gestión nacional en cuanto a infraestructura, administración del ciclo de vida del software y gestión del conocimiento. Entre los métodos empíricos más empleados se destaca la observación participante, el análisis documental y la encuesta y entre los teóricos el histórico-lógico, análisis-síntesis e inductivo-deductivo. Los resultados muestran que la gestión del Proceso de Desarrollo del Software Educativo (PDSE) ha constituido una necesidad histórica en el de cursar de la EMS y un proceso en continuo perfeccionamiento(AU)

Educational software has been a need in the transformations of medical superior education to make tuitional process perfect learning, work exposes the more outstanding characteristics of three stages that he has transited for his national steps as to infrastructure, administration of life cycle of the software and steps of knowledge. Enter empiric further methods used participating observation stands out, documentary analysis and the opinion poll and among the theorists the historic logician, analysis synthesis and inductive deductive. Aftermath evidence that the Educative Software Process Development steps has constituted a historic need in the EMS's in the time and a process in continuous perfecting(AU)

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El empleo del software educativo ha constituido una exigencia en las transformaciones que en la Educación Médica Superior (EMS) en Cuba han tenido lugar para perfeccionar el Proceso de Enseñanza Aprendizaje (PEA). Al respecto el trabajo expone las características más sobresalientes de las tres etapas por las que ha transitado su gestión nacional en cuanto a infraestructura, administración del ciclo de vida del software y gestión del conocimiento. Entre los métodos empíricos más empleados se destaca la observación participante, el análisis documental y la encuesta y entre los teóricos el histórico-lógico, análisis-síntesis e inductivo-deductivo. Los resultados muestran que la gestión del Proceso de Desarrollo del Software Educativo (PDSE) ha constituido una necesidad histórica en el de cursar de la EMS y un proceso en continuo perfeccionamiento(AU)

Educational software has been a need in the transformations of medical superior education to make tuitional process perfect learning, work exposes the more outstanding characteristics of three stages that he has transited for his national steps as to infrastructure, administration of life cycle of the software and steps of knowledge. Enter empiric further methods used participating observation stands out, documentary analysis and the opinion poll and among the theorists the historic logician, analysis synthesis and inductive deductive. Aftermath evidence that the Educative Software Process Development steps has constituted a historic need in the EMS's in the time and a process in continuous perfecting(AU)

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RSAT (Regulatory Sequence Analysis Tools) is a suite of modular tools for the detection and the analysis of cis-regulatory elements in genome sequences. Its main applications are (i) motif discovery, including from genome-wide datasets like ChIP-seq/ATAC-seq, (ii) motif scanning, (iii) motif analysis (quality assessment, comparisons and clustering), (iv) analysis of regulatory variations, (v) comparative genomics. Six public servers jointly support 10 000 genomes from all kingdoms. Six novel or refactored programs have been added since the 2015 NAR Web Software Issue, including updated programs to analyse regulatory variants (retrieve-variation-seq, variation-scan, convert-variations), along with tools to extract sequences from a list of coordinates (retrieve-seq-bed), to select motifs from motif collections (retrieve-matrix), and to extract orthologs based on Ensembl Compara (get-orthologs-compara). Three use cases illustrate the integration of new and refactored tools to the suite. This Anniversary update gives a 20-year perspective on the software suite. RSAT is well-documented and available through Web sites, SOAP/WSDL (Simple Object Access Protocol/Web Services Description Language) web services, virtual machines and stand-alone programs at http://www.rsat.eu/.

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Since the introduction of CT colonography (CTC) in the mid-1990s, there have been continuous advancements in the examination technique and advanced visualization software for interpretation. This review will cover the origins of CTC as a natural extension of abdominal CT imaging, and discuss the evolution of CTC through the subsequent clinical phases of feasibility, validation, and implementation.

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CONTEXTO: O reconhecimento da termoablação endovenosa como tratamento da insuficiência de veias safenas traz a necessidade de maior conhecimento e compreensão do método. A densidade de energia endovenosa linear (linear endovenous energy density – LEED) é a variável mais aceita para padronização, cada vez mais amplamente divulgada. Não deve ser utilizada apenas para comparação de resultados científicos deve também ser usada no intraoperatório para a realização do procedimento com segurança. OBJETIVOS: Desenvolver aplicativo para mensuração da LEED e avaliar sua aplicabilidade. MÉTODOS: O aplicativo para iOS EVLTraining® foi desenvolvido para equipamentos portáteis com o intuito de padronizar a emissão energética em procedimentos de termoablação endovenosa. RESULTADOS: O aplicativo criado mostrou equivalência com as medidas aplicadas no procedimento cirúrgico. CONCLUSÕES: O software EVLTraining® permite o treino prévio de cirurgião e equipe para a velocidade de tração da fibra ótica que será aplicada.

BACKGROUND: Recognition of endovenous thermal ablation as a treatment for saphenous vein insufficiency brings a need for greater knowledge and understanding of the method. Linear endovenous energy density (LEED) is the most accepted variable for standardization and it has been covered in a growing number of publications. However, it should not exclusively be used for comparison of scientific results, it should also be used intraoperatively so that the procedure is conducted safely. OBJECTIVES: To develop a mobile app for measurement of LEED and evaluate its applicability. METHOD: The application for iOS EVLTraining® was developed for portable devices in order to standardize energy emission in endovenous thermal ablation procedures. RESULTS: The application developed demonstrated equivalence to measures applied during surgical procedures. CONCLUSION: The EVLTraining® software enables surgeons and staff to train the optical fiber pullback speed to be applied prior to surgery.

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Dr. Joseph Lau is a world-leading expert in meta-analysis and systematic reviews. Currently a professor in the Department of Health Services, Policy and Practice and co-director of the Center for Evidence-based Medicine at Brown University, Professor Lau has applied evidence-based methods to a variety of clinical, biomedical and healthcare topics; has developed reliable and efficient methods and tools to conduct systematic reviews and meta-analyses; and has advanced an understanding on the impact of factors that may contribute to differences of results in scientific studies. His past research includes cumulative meta-analysis of randomized controlled trials, comparison of results from large trials and meta-analyses of small trials, effect of baseline risk in the interpretation of clinical trial results, and empirical evaluation of existing methods of combining data. His current focus is on a Web-based repository of systematic review data, reviews of diagnostic tests, nutrition, clinical practice guidelines, and dissemination of evidence-based methods to varied health-care disciplines. This report is a conversation from an adapted version of an interview, more or less chronologically arranged, between Joseph C. Cappelleri as interviewer and Joseph Lau as interviewee, with Meghan Ingerick recording and transcribing the interview.

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We present a review of the historical evolution of software engineering, intertwining it with the history of knowledge engineering because "those who cannot remember the past are condemned to repeat it." This retrospective represents a further step forward to understanding the current state of both types of engineerings; history has also positive experiences; some of them we would like to remember and to repeat. Two types of engineerings had parallel and divergent evolutions but following a similar pattern. We also define a set of milestones that represent a convergence or divergence of the software development methodologies. These milestones do not appear at the same time in software engineering and knowledge engineering, so lessons learned in one discipline can help in the evolution of the other one.

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For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.

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I provide a selective review of the literature on the multiple testing problem in fMRI. By drawing connections with the older modalities, PET in particular, and how software implementations have tracked (or lagged behind) theoretical developments, my narrative aims to give the methodological researcher a historical perspective on this important aspect of fMRI data analysis.

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Since the mid 1960s, researchers in computer science have famously referred to chess as the 'drosophila' of artificial intelligence (AI). What they seem to mean by this is that chess, like the common fruit fly, is an accessible, familiar, and relatively simple experimental technology that nonetheless can be used productively to produce valid knowledge about other, more complex systems. But for historians of science and technology, the analogy between chess and drosophila assumes a larger significance. As Robert Kohler has ably described, the decision to adopt drosophila as the organism of choice for genetics research had far-reaching implications for the development of 20th century biology. In a similar manner, the decision to focus on chess as the measure of both human and computer intelligence had important and unintended consequences for AL research. This paper explores the emergence of chess as an experimental technology, its significance in the developing research practices of the AI community, and the unique ways in which the decision to focus on chess shaped the program of AI research in the decade of the 1970s. More broadly, it attempts to open up the virtual black box of computer software--and of computer games in particular--to the scrutiny of historical and sociological analysis.

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