AI Medical Compendium

Development of Venous Thromboembolism Risk Prediction Models Based on Whole Blood Gene Expression Profiling Using 20 Machine Learning Algorithms: Comprehensive Analysis Study.

JMIR medical informatics Jan 16, 2026

BACKGROUND: There is a lack of venous thromboembolism (VTE) risk prediction models based on gene expression information. OBJECTIVE: This study aimed to construct a VTE prediction model based on whole blood gene expression profiling, by performing a c... read more

Humans Machine Learning Algorithms Female Risk Factors Male Middle Aged Risk Assessment Gene Expression Profiling ROC Curve Venous Thromboembolism

Learning the anatomical topology consistency driven by Wasserstein distance for weakly supervised 3D pancreas registration in multi-phase CT images.

Biomedical physics & engineering express Jan 16, 2026

Accurate and automatic registration of the pancreas between contrast-enhanced CT (CECT) and non-contrast CT (NCCT) images is crucial for diagnosing and treating pancreatic cancer. However, existing deep learning-based methods remain limited due to in... read more

Magnetic resonance imaging-based proton dose calculation for pelvic tumors using deep learning.

Physics in medicine and biology Jan 16, 2026

Objective Magnetic resonance imaging (MRI)-only proton therapy combines high soft tissue contrast with high-precision dose distributions. However, conventional dose calculation is impossible on MRI due to missing electron density information. Thi... read more

Institution-specific pre-treatment quality assurance control and specification limits: a tool to implement a new formalism and criteria optimization using statistical process control and heuristic methods.

Physics in medicine and biology Jan 16, 2026

OBJECTIVE: Establishing control and specification limits for Volumetric Modulated Arc Therapy (VMAT) pre-treatment quality assurance (PTQA) is essential for streamlining PTQA workflows and optimizing plan complexity. This study aimed to develop and i... read more

Barriers and facilitators to implementing the living guideline development framework in oncology: a mixed methods study.

BMJ open Jan 16, 2026

OBJECTIVE: To explore stakeholder experiences with implementing the living guideline (LG) development framework in oncology, and to identify barriers, facilitators and solutions to support its uptake and sustainability. DESIGN: An exploratory sequent... read more

Humans Female Cross-Sectional Studies Male Neoplasms Qualitative Research Surveys and Questionnaires Interviews as Topic Medical Oncology Practice Guidelines as Topic Stakeholder Participation

A scalable computational framework for predicting gene expression from candidate cis-regulatory elements.

Genome research Jan 16, 2026

Deciphering the relationships between cis-regulatory elements (CREs) and target gene expression has been a long-standing unsolved problem in molecular biology, and the dynamics of CREs in different cell types make this problem more challenging. To ad... read more

Artificial intelligence-based fluid quantification predicts clinical outcomes in diabetic macular oedema eyes treated with intravitreal dexamethasone implants: DIADEMA project.

The British journal of ophthalmology Jan 16, 2026

AIM: To explore associations between artificial intelligence (AI)-based baseline optical coherence tomography (OCT) fluid compartment quantifications and 12-month visual outcomes in diabetic macular oedema (DME) eyes treated with the intravitreal dex... read more

Correction in: Artificial Intelligence-Assisted Capsule Endoscopy Versus Conventional Capsule Endoscopy for Detection of Small Bowel Lesions: A Systematic Review and Meta-Analysis.

Journal of gastroenterology and hepatology Jan 16, 2026

Deconstruction by C. thermocellum-from microbe mediated to dynamic redistribution of cellulosomes.

Life science alliance Jan 16, 2026

Clostridium thermocellum is one of the most efficient microorganisms for the deconstruction of cellulosic biomass. To achieve this high level of cellulolytic activity, C. thermocellum uses large multienzyme complexes known as cellulosomes to break do... read more

Biomass Cellulose Cell Wall Acetivibrio thermocellus Cellulosomes

Development and external validation of machine learning approaches for risk prediction of cardiovascular disease in individuals with schizophrenia: a nationwide Swedish and Danish study.

BMJ mental health Jan 16, 2026

BACKGROUND: Currently available cardiovascular disease (CVD) risk prediction tools may underestimate the risk in individuals with schizophrenia. OBJECTIVE: To develop and externally validate 5-year CVD risk prediction models for people with schizophr... read more

Humans Machine Learning Female Sweden Aged Adult Male Cardiovascular Diseases Middle Aged Risk Assessment Denmark Registries Schizophrenia

Artificial Intelligence Medical Compendium