Artificial Intelligence Medical Compendium

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

Showing 741 to 750 of 200,021 articles

Utilizing artificial intelligence and geospatial analysis to examine the urban built environment, social vulnerability, and child neglect in Los Angeles.

Child abuse & neglect
BACKGROUND: Child neglect, defined as a parent or guardian's failure to provide basic needs such as food, clothing, shelter, or medical care, is a widespread global public health issue with long-term consequences for child development. OBJECTIVE: To ... read more 

Integrating machine learning with QSPR for property prediction of anti-vertigo drugs.

Computational biology and chemistry
Vertigo is a debilitating vestibular disorder affecting approximately 10-30% of the global population, yet no dedicated computational chemistry study has systematically characterised the properties of its pharmacological agents using machine learning... read more 

A reproducible data-driven parameter optimization framework for classical skull stripping methods across heterogeneous brain MRI datasets.

Biomedical physics & engineering express
Accurate skull stripping is a critical preprocessing step for reliable brain MRI analysis, yet the performance of classical algorithms remains highly sensitive to parameter selection. This study proposes a statistically reproducible, dataset-level pa... read more 

Designing the Future of Hemostasis.

Seminars in thrombosis and hemostasis
Bleeding disorders arising from dysfunctional platelet-protein interactions pose a significant clinical challenge due to their heterogeneity and complexity. Primary hemostasis is mediated by von Willebrand factor (VWF) and platelet surface receptors ... read more 

Prediction of Ligand Binding to Transthyretin Using Machine Learning Algorithms and Low-Dimensional Molecular Descriptors: A Tox24 Challenge Study.

Chemical research in toxicology
This study presents a comprehensive machine learning approach for predicting the percent displacement of ANSA from human transthyretin (TTR) at fixed assay conditions as defined in the Tox24 Challenge. TTR is a critical serum transport protein for th... read more 

Bridging Generations: Leveraging Technology and Artificial Intelligence for Better Research, Outreach, and Daily Practice.

The Journal of rheumatology
The Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) 2025 annual meeting hosted a workshop entitled "Bridging generations: leveraging technology and AI for better research, outreach, and daily practice." This interactiv... read more 

Unequal harvests: AI-assisted evidence map of trends and gaps in global farmer health research along SDG 3 priorities.

BMJ open
INTRODUCTION: Ensuring the health of agricultural workers, the world's largest labour force, is key for sustainable food production and progress towards the Sustainable Development Goals (SDGs). METHODS: We conducted an artificial intelligence (AI)-a... read more 

From Parasite to Pill: Harnessing Biology for Breakthroughs in Antimalarial Drug Discovery.

Cold Spring Harbor perspectives in medicine
The global imperative for malaria eradication demands innovative strategies for antimalarial drug discovery, particularly in the face of growing drug resistance. This article describes how biological insights into Plasmodium parasites and their inter... read more 

Problem-based learning in the age of generative AI: A structured blueprint for medical curricula.

Zeitschrift fur Evidenz, Fortbildung und Qualitat im Gesundheitswesen
BACKGROUND: Problem-based learning (PBL) is a well-established approach in medical education. In small groups, students work on real clinical cases with a high level of self-responsibility. Rooted in constructivist learning theory and the Socratic me... read more 

Differentiating Mummified Thyroid Nodules From Papillary Thyroid Carcinoma: A Machine Learning Approach Using Multi-Modal Ultrasound Radiomics.

Ultrasound in medicine & biology
OBJECTIVES: This study aimed to establish a machine-learning model that integrates contrast-enhanced ultrasound (CEUS) radiomics, conventional ultrasound (US) radiomics and clinical features for distinguishing mummified thyroid nodules (MTNs) from pa... read more