Latest AI in Medicine Research | AI Medical Compendium

Predicting cardiovascular diseases using imbalanced data: An XGBoost-based analysis of the 2022 BRFSS dataset.

American heart journal plus : cardiology research and practice Jan 10, 2026

BACKGROUND: Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, arising from complex interactions among demographic, clinical, behavioral, and social determinants. Leveraging large, nationally representative datasets such ... read more

A clinical dataset on type-2 diabetes including demographic, anthropometric, and biochemical parameters from Bangladesh.

Data in brief Jan 10, 2026

Type-2 diabetes is a major public health concern in Bangladesh, and this dataset provides 1065 curated patient records with demographic, anthropometric, and clinical variables relevant to its assessment. The data were collected during routine clinica... read more

Deep-sea image dataset for organism detection.

Data in brief Jan 10, 2026

The conservation of marine resources and the mitigation of marine pollution require strengthened knowledge of marine biodiversity, particularly in the deep sea. Videos and images are valuable for documenting the distribution of deep-sea organisms, bu... read more

Application and validation of AI-driven methods to explore patient experiences of pre-cervical cancer.

European journal of obstetrics, gynecology, and reproductive biology Jan 10, 2026

OBJECTIVE: We sought to apply novel natural language processing (NLP) tools to explore patient experiences of pre-cervical cancer on social media and validate the performance of these tools. METHODS: All posts and comments were extracted from the for... read more

Multi-scale heart simulation augments the explainability of artificial intelligence-enabled electrocardiogram through provision of an electrocardiogram database labelled with cellular pathologies.

Computer methods and programs in biomedicine Jan 10, 2026

BACKGROUND AND OBJECTIVES: Although artificial-intelligence-enhanced electrocardiograms (AI-ECGs) offer prediction and diagnosis capabilities superior to those of humans, they exhibit poor explainability and interpretability because of their complex-... read more

An old disease, a new linguistic challenge for large language models: patient education on psoriasis and psoriatic arthritis in an underrepresented medical language.

International journal of medical informatics Jan 10, 2026

OBJECTIVE: Large Language Models (LLMs) are increasingly applied to patient education, yet their performance in languages that are relatively underrepresented in medical-domain corpora and large language model training datasets remains underexplored.... read more

Automated extraction of fluoropyrimidine treatment and treatment-related toxicities from clinical notes using natural language processing.

International journal of medical informatics Jan 10, 2026

OBJECTIVE: Fluoropyrimidines are widely prescribed for colorectal and breast cancers, but are associated with toxicities such as hand-foot syndrome and cardiotoxicity. Since toxicity documentation is often embedded in clinical notes, we aimed to deve... read more

The answer lies within: Detecting Trojans from DNNs' inherent characteristics.

Neural networks : the official journal of the International Neural Network Society Jan 10, 2026

Deep neural networks (DNNs) are vulnerable to Trojan attacks, where adversaries implant Trojans that cause DNNs to misbehave when encountering specific triggers. Detecting Trojans in DNNs is crucial to mitigate potential safety risks. Traditional met... read more

Unlocking 2D/3D+T myocardial mechanics from cine MRI: a mechanically regularized space-time finite element correlation framework.

Medical image analysis Jan 10, 2026

Accurate and biomechanically consistent quantification of cardiac motion remains a major challenge in cine MRI analysis. While classical feature-tracking and recent deep learning methods have improved frame-wise strain estimation, they often lack bio... read more

A causal bidirectional selective state space model for imaging genetics in neurodegenerative diseases.