Artificial Intelligence Medical Compendium

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

Showing 70,151 to 70,160 of 234,131 articles

Research on a novel gene sequence prediction and homomorphic encryption method based on Mamba-VMD.

Computational biology and chemistry Nov 11, 2025
Gene sequence prediction not only effectively identifies homologous genes but also provides crucial insights into gene function and evolutionary relationships, making it one of the significant research directions in the field of bioinformatics. Given... read more 

Machine learning-accelerated 1H NMR quantification for bioprocess metabolite monitoring in monoclonal antibody production.

Journal of pharmaceutical and biomedical analysis Nov 11, 2025
Monitoring of metabolite dynamics during cell culture process is crucial for ensuring consistent monoclonal antibody (mAb) yield and quality. While proton nuclear magnetic resonance (1H NMR) offers an ideal solution for process monitoring due to its ... read more 

Artificial Intelligence in Surgical Education: A 2025 Update on Adaptive Training, Feedback, and Competency-Based Education.

The American surgeon Nov 11, 2025
In the rapidly advancing landscape of surgical education, the traditional apprenticeship model is being increasingly complemented by individualized learning, competency-based assessment, and data-driven feedback. Work-hour restrictions, administrativ... read more 

An educational tool using artificial-intelligence-generated visualisations to improve teaching of psychiatric symptom characterisation.

The British journal of psychiatry : the journal of mental science Nov 11, 2025
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Machine Learning-Based Risk Prediction for Feline Mammary Tumours: A Comprehensive Epidemiological Analysis Using Multi-Model Ensemble Approach.

Veterinary and comparative oncology Nov 11, 2025
Feline mammary tumours represent the third most common malignancy in cats, with limited evidence-based tools available for risk assessment and screening guidance. Traditional veterinary approaches rely on subjective clinical judgement, lacking quanti... read more 

Ambient Artificial Intelligence in Hand Surgery: Insights, Pearls, and Pitfalls From Real-World Use.

Hand (New York, N.Y.) Nov 11, 2025
BACKGROUND: Documentation burden is a major contributor to surgeon burnout, particularly in high-volume outpatient specialties such as hand surgery. These encounters often involve multiple concurrent diagnoses, procedural planning, and longitudinal c... read more 

Machine learning versus traditional formulas for fetal weight estimation: An international multicenter study evaluating prediction accuracy across birth weight percentiles.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics Nov 11, 2025
OBJECTIVE: To assess whether machine learning (ML) offers improved birth weight prediction accuracy, since despite numerous models, the Hadlock formula remains the clinical standard. METHODS: A multicenter retrospective study analyzed data from 9674 ... read more 

Development and validation of a multiphase computed tomography-based radiomics classifier for differentiating retroperitoneal non-fatty dedifferentiated liposarcoma from leiomyosarcoma.

Abdominal radiology (New York) Nov 11, 2025
OBJECTIVE: We aimed to develop and internally validate a radiomics classification model based on multiphase computed tomography (CT) scans for preoperative differentiation of retroperitoneal non-fatty dedifferentiated liposarcoma (DDL) from leiomyosa... read more 

18F-FDG PET-based ensemble deep learning model for the prediction of lymphovascular invasion in colorectal cancer patients.

Abdominal radiology (New York) Nov 11, 2025
OBJECTIVE: The aim of this study was to investigate the diagnostic performance of the 2.5-dimensional (2.5D) ensemble deep learning (DL) model based on 18F-fuorodeoxyglucose (FDG) positron emission tomography (PET) images in predicting lymphovascular... read more 

Deep learning for automatic detection of hepatocellular carcinoma in dynamic contrast-enhanced MRI.

Abdominal radiology (New York) Nov 11, 2025
OBJECTIVE: Develop a deep learning model for automatic hepatocellular carcinoma (HCC) detection in T1 weighted imaging (WI) Dynamic Contrast-Enhanced (DCE) liver MRI using extracellular contrast agent, and to analyze its performance at both patient a... read more 
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