± HEALTH Colorectal Cancer (CRC) is a common cause of cancer death and prognostic factors are used to determine manage…+ HEALTH This multicenter study developed and validated an interpretable machine learning model integrating granular n…+ HEALTH Multiple stakeholders need to locate results of registered clinical trials but frequently struggle to find th…+ HEALTH Accurate preoperative glioma grading and molecular subtyping are important for treatment. The vascular microe…+ HEALTH Gastrointestinal endoscopy generates extensive high-resolution video data, posing significant challenges for…+ HEALTH Non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) and invasive encapsulat…+ POLICY Artificial intelligence (AI) has the potential to strengthen real-world evidence (RWE) for regulatory decisio…± HEALTH Echocardiography remains the cornerstone of cardiovascular imaging. However, traditional workflows including…
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877 published stories · page 46 of 59

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Predicting Biomolecular Interactions in the Next Decade: Physics-Based Methods Meet AI-Driven Approaches

The quantitative prediction of biomolecular recognition is crucial to molecular science. The challenge is not merely structural determination but the prediction of (thermo)dynamic and kinetic observables arising from high-dimensional molecular ensembles, such as free energies, conformational distributions, and rate processes across different conditions. As the field shifts from structure-centric to ensemble-based descriptions, two complementary modeling strategies have matured: explicit energy-based approaches g…

The Journal of Physical Chemistry Letters · Science

Predicting Biomolecular Interactions in the Next Decade: Physics-Based Methods Meet AI-Driven Approaches
Machine learning force fields for inorganic crystalline materials: principles, advances, and emerging applications
Both readings

Machine learning force fields for inorganic crystalline materials: principles, advances, and emerging applications

Machine learning force fields (MLFFs) combine the high accuracy of first-principles methods with the high efficiency of classical force fields, offering new opportunities for atomic-level studies of inorganic crystalline materials. We systematically summarize the research progress on MLFFs, elucidate their fundamental principles and developmental history, and categorically introduce the technical characteristics of representative models and relevant benchmarking platforms. We aim to review the advantages of MLFF…

Science
Robert Laidlow: Reality Eaters album review
Evidence-backed problem

Robert Laidlow: Reality Eaters album review

Robert Laidlow is as at home in the realms of science and technology as he is in the world of classical music. As this NMC debut album demonstrates, his intricate, wildly imaginative work is eminently approachable, even if the core concepts are highly complex. Warp, a terse, 12-minute piano concerto, proposes a musical solution to Einstein’s field equations as the intrepid Joseph Havlat boldly goes where no pianist has gone before amid the distorting fabric of orchestral space-time. Strident orchestral lines spi…

Media & Arts
Musk’s SpaceX courts retail investors as it aims for record-breaking stock market flotation
Evidence-backed gain

Musk’s SpaceX courts retail investors as it aims for record-breaking stock market flotation

SpaceX will kick off the marketing for its highly anticipated stock exchange debut by hosting an event in June for 1,500 retail investors, as executives set out to convince buyers that the aerospace to artificial intelligence group should be valued at $2tn. In an unusual move, the company has earmarked a large portion of its shares – potentially up to 30% – for non-professional, non-institutional investors, banking on the popularity of its chief executive, Elon Musk, to help it raise $75bn (about £56bn) in what…

Business
Legal Foundations for the Application OF Artificial Intelligence Technologies in the Sports Industry
Evidence-backed problem

Legal Foundations for the Application OF Artificial Intelligence Technologies in the Sports Industry

The integration of Artificial Intelligence (AI) technologies in the sports industry has brought about significant advancements in performance analysis, fan engagement, and decision-making processes. However, this rapid adoption of AI also raises complex legal challenges that require careful consideration. This article examines the legal foundations and implications of applying AI technologies in the sports industry. Through a comprehensive analysis of existing legal frameworks, case studies, and potential future…

Sports

Application of Artificial Intelligence in Real-Time Strategic Decision Support System for Sports Competitions

Various high-tech technologies are used extensively around the world in sports competitions especially in athletic events where scientific real-time decision-making is essential to improve competitive efficiency and match outcomes. This research proposes the introduction of the concept of entropy by applying the ID3 algorithm with the use of the attribute entropy value change as the selection criterion to develop the decision tree model for real-time sports competition data processing. Meanwhile, an enhanced Mon…

Sports
Application of Artificial Intelligence in Real-Time Strategic Decision Support System for Sports Competitions

Beyond BMI: Deep Learning Segmentation-Driven CT Reveals Body Composition Changes after Metabolic and Bariatric Surgery

Background BMI is the primary metric used to evaluate outcomes of metabolic and bariatric surgery (MBS), but it does not distinguish tissue compartments or quantify visceral adiposity (VAT), a key determinant of cardiometabolic risk. We evaluated the relationship between BMI and VAT and characterized compartment-specific remodeling after MBS using artificial intelligence-enabled CT segmentation. Study design A retrospective analysis of prospectively collected abdominal CT scans was performed at a single tertiary…

Health
Beyond BMI: Deep Learning Segmentation-Driven CT Reveals Body Composition Changes after Metabolic and Bariatric Surgery

Medical student reliance on artificial intelligence in nephrology education

Background Large language models such as ChatGPT are increasingly used in medical education and may influence student learning and decision-making. Despite strong performance on factual recall, limitations in clinical reasoning raise concerns about how learners engage with artificial intelligence (AI)-generated recommendations, particularly in challenging domains such as renal physiology, where foundational understanding underpins clinical application. Methods Fifty-seven first-year medical students completed 24…

Health
Medical student reliance on artificial intelligence in nephrology education

Creative partnerships with generative AI. Possibilities for education and beyond

• Generative AI's role in creative production is accelerating, demanding new interaction models between humans and machines. • The authors explore human-AI creative production with ChatGPT and analyse outputs using the concept of alterity relations. • The findings present profound implications for reimagining the essence of creative outputs in education and creative industries. • AI's potentially transformative role as a collaborative partner in fostering creativity and innovation in education. The impact of gen…

Education
Creative partnerships with generative AI. Possibilities for education and beyond