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1338 published stories · page 28 of 90

HealthEvidence-backed problem

Artificial intelligence and ultra-high performance computing methods and experiments for drug discovery: virtual screening, deep learning, molecular dynamics simulations, ADMET modelling, and experimental validation

Recent years have witnessed considerable progress in computer-aided drug discovery, driven by the incorporation of computational technologies within both academic and pharmaceutical environments. This evolution is marked by a significant accumulation of data pertaining to detailed three-dimensional structural information, ligand properties, and their interactions with therapeutic targets. The augmentation of computational capabilities and the accessibility of extensive chemical libraries containing billions of d…

Molecular Biomedicine

Evidence-backed gain

Development of a Machine Learning Algorithm for Differential Diagnosis Between Primary Immune Thrombocytopenia and Connective Tissue Disease-Related Thrombocytopenia in Pediatric Patients

Evidence-backed problem

Machine learning models for early detection of urinary tract infections in kidney transplant patients

Evidence-backed problem

SlideChat is a multimodal generative artificial intelligence assistant for whole-slide computational pathology across cancer types

Evidence-backed problem

Ethical Considerations on Artificial Intelligence, Health and Health Care. All That Glisters Is Not Gold

Background Artificial intelligence (AI) is transforming global health care through innovations in deep learning, generative models and agentic AI systems. Traditional reductionist approaches to complex pathophysiological pathways fail to capture the true complexity of disease, motivating the adoption of network medicine (NM), which models biological systems as dynamic, interconnected networks. When combined with AI, NM enables integration of multiomic data and better characterizes disease mechanisms to guide pre…

Evidence-backed problem

Clinical Applications of Artificial Intelligence in Cardiac CT: From Coronary CT Angiography to CT-Derived Fractional Flow Reserve and Myocardial Perfusion Imaging

Artificial intelligence (AI) has rapidly transformed cardiac CT, extending its clinical utility from coronary CT angiography (CCTA) to CT myocardial perfusion imaging (CT-MPI). This review outlines the current advances in and future perspectives on AI-aided cardiac CT across anatomical, functional, and prognostic dimensions. In CCTA, AI can automate calcium scoring, vessel segmentation, and plaque characterization, markedly improving workflow efficiency and reproducibility. Deep-learning models can allow accurat…

Evidence-backed gain

Explainable AI-Supported Cyber-Physical Collaboration for Sustainable Manufacturing in Industry 5.0

In this study, we present an innovative approach to the sustainable manufacturing of industrial parts using an explainable artificial intelligence (XAI)- based cyber-physical collaboration system for Industry 5.0. Current cyber-physical human systems (CPHSs) have been found to integrate AI only to a limited extent and often lack explainability. Consequently, there is a need to improve their scalability and flexibility, in keeping with the tenets of Industry 5.0: resilience, long-term viability, and human-centric…

Evidence-backed gain

A polyline searching-driven evolutionary AI for disease detection of medical imaging data

Objective. Accurate Ultrasound (US) prostate cancer (PCa) segmentation images hold significant value for organ interventional guidance and clinical disease diagnosis. However, this task still poses substantial challenges. The main obstacles include blurred or incomplete boundaries separating PCa from adjacent soft tissues, shadow artifacts inherent to ultrasound imaging, and drastic inter-patient variations in organ morphological shapes. Approach . To address these issues, our method introduces a novel coarse-to…

Lifestyle

Explainable and domain-adaptive prediction models for refrigerant charging in air conditioning systems within industrial processes

Accurate prediction of refrigerant deficiency in consumer air conditioning (AC) systems is critical for optimizing energy efficiency and operational stability. However, existing data-driven models often suffer from significant performance degradation due to domain shift across different AC types and a lack of explanatory transparency. To address these challenges, we propose AC-RPX (AC-Refrigerant Prediction eXplainable AI), a unified framework that integrates a Domain Encoder augmented with domain-specific token…

Health

Methodological Reporting Quality of Artificial Intelligence-Based Orthopedic Studies: A Literature Analysis

Objective We set out to examine how completely artificial intelligence (AI)-based orthopedic studies report their methods. Methods A PubMed search covering 2023-2025 was run with a predefined strategy. Screening of titles, abstracts and full texts left 280 eligible papers, and 200 of these were drawn at random for scoring. Each paper was rated against a six-item framework built from the TRIPOD-AI, STARD-AI and CONSORT-AI guidelines. Results Mean score across the 200 studies was 4.8±0.9. Twenty-eight percent reac…

Business

Implementation of a passive bin-based perpetual medication inventory model within ambulatory clinics at an academic medical center

Purpose Ambulatory clinics manage high-cost medications with little visibility into quantity or movement, leaving unrealized opportunities for inventory optimization. Automated dispensing cabinets, common in inpatient settings, address this issue but require significant capital investment, forcing clinics into complex workflows to balance demand for high-cost medications with minimizing waste. This study evaluated a passive bin-based inventory model that tracked clinic transactions in real time using light senso…

Policy

Multimodal Graph Neural Networks and Evolutionary Knowledge Fusion for Secure and Explainable Governance in Intelligent IoT Interactive Media Systems

This research proposes a secure, explainable, and context-aware governance framework for blockchain-based digital media contracts in multimodal artificial intelligence-enabled AIoT interactive systems. As digital licensing, NFT copyright management, royalty distribution, and cross-chain content circulation become increasingly embedded in smart media ecosystems, existing contract auditing approaches remain limited by unimodal analysis, weak explainability, black-box decision processes, and insufficient cross-plat…

Health

Post-traumatic Psychopathology and Cardiovascular Risk: A Danish Case-Control Study of Sex-Specific Associations

Background There is increasing recognition that trauma exposure and related psychiatric consequences predict cardiovascular disease risk. However, most research has specifically examined post-traumatic stress disorder-despite evidence that a range of psychiatric disorders may follow trauma. We applied machine learning to identify key post-traumatic psychiatric predictors of incident major adverse cardiac and cerebrovascular events (MACCE) in a population-based cohort. Methods We conducted a case-control study of…

Health

A strategic pathway for the ethical development of AI tools in dementia care

Artificial intelligence (AI) is rapidly entering dementia clinical practice, offering opportunities across the care continuum. However, cognitive decline creates a unique ethical challenge. This perspective article proposes a strategy to ensure the responsible development and deployment of AI tools for dementia. An interdisciplinary workgroup of the Alzheimer's Association Innovation Roundtable synthesized ethical frameworks, regulatory standards, and empirical evidence to generate expert consensus. The result i…

Health

Artificial intelligence-assisted histopathological diagnosis of endocervical gastric-type adenocarcinoma: a multicenter model development and validation study

Endocervical gastric-type adenocarcinoma (GAS) is one of the most aggressive subtypes of cervical cancer and is frequently underdiagnosed due to morphological ambiguity, leading to delayed diagnosis. Despite the availability of molecular and genomic assays, their high cost, complexity, and limited reproducibility restrict clinical use. This study therefore proposes a highly sensitive artificial intelligence (AI)-assisted diagnostic system for GAS based exclusively on H&E-stained histopathological images. We incl…