Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 55,141 to 55,150 of 226,647 articles

Transforming MOF Modeling with Machine-Learned Potentials: Progress and Perspectives.

Journal of chemical information and modeling Feb 3, 2026
Machine-learned potentials (MLPs) have emerged as transformative tools for modeling metal-organic frameworks (MOFs), bridging the accuracy of quantum mechanics with the efficiency required for large-scale molecular simulations. By learning the potent... read more 

Dynamic Polaronic Control of Metal Cluster Adaptability on Reducible Oxides.

Journal of the American Chemical Society Feb 3, 2026
Metal-oxide interactions are ubiquitous in many technological applications and involve a complex interplay between the oxide support and the metal nanoparticle. Particularly, it has been proposed that in strong metal-support interaction, the defect c... read more 

Adoption intentions and barriers to emerging technologies among people with disabilities: a systematic review of attitudes, accessibility, and inclusion.

Disability and rehabilitation. Assistive technology Feb 3, 2026
PURPOSE: Emerging technologies, ranging from robotics and artificial intelligence to assistive innovations, hold transformative potential for improving the quality of life among people with disabilities. Yet, despite decades of research, systematic e... read more 

Foundations for AI-assisted Adverse Outcome Pathways (AOPs) in radiation research.

International journal of radiation biology Feb 3, 2026
PURPOSE: Artificial Intelligence (AI) and Machine Learning (ML) are being explored to improve systematic evidence gathering and to identify patterns across datasets. Their integration into the development of radiation Adverse Outcome Pathways (AOPs) ... read more 

Digital twin-assisted surgery: technological architecture, integration across surgical phases, implementation challenges and future directions.

International journal of surgery (London, England) Feb 3, 2026
Digital twin-assisted surgery referred to the use of a dynamic, patient specific virtual model that mirrored physical patient in real time to enhance surgical planning, guidance, and outcomes. This emerging approach integrated data from robotic manip... read more 

TabPFN-driven ternary classification of stage IA lung adenocarcinoma subtypes using AI-derived histogram features a retrospective multicenter cohort study.

International journal of surgery (London, England) Feb 3, 2026
BACKGROUND: Preoperative differentiation of precursor glandular lesions (PGL), minimally invasive (MIA), and invasive adenocarcinoma (IAC) in stage IA lung adenocarcinoma (LUAD) is critical for surgical planning but remains challenging due to overlap... read more 

Comment on "Deep learning habitat radiomics based on ultrasound for predicting preoperative locally progression and postoperative recurrence risk of thyroid cancer: a multicenter study".

International journal of surgery (London, England) Feb 3, 2026
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Deep Learning-Powered Scalable Cancer Organ Chip for Cancer Precision Medicine.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Feb 3, 2026
Functional precision oncology complements genomic approaches by directly testing treatment options on patient-derived models. However, existing platformssuch as patient-derived xenografts (PDXs) and patient-derived organoids (PDOs), face major barrie... read more 

Fairness Correction in COVID-19 Predictive Models Using Demographic Optimization: Algorithm Development and Validation Study.

Online journal of public health informatics Feb 3, 2026
BACKGROUND: COVID-19 forecasting models have been used to inform decision-making around resource allocation and intervention decisions, such as hospital beds or stay-at-home orders. State-of-the-art forecasting models often use multimodal data, inclu... read more 

Spectral Decomposition of Chemical Semantics for Activity Cliffs-Aware Molecular Property Prediction.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Feb 3, 2026
Accurately predicting physicochemical and biological properties of molecules is vital for modern drug discovery, yet existing deep learning models struggle to replicate the multi-level reasoning of chemists. Relying on single molecular graphs, they f... read more 
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