Artificial Intelligence Medical Compendium

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

Showing 37,121 to 37,130 of 223,469 articles

Comparative Performance of Artificial Intelligence-Based Computer-Aided Detection Systems for Colorectal Polyps: A Systematic Review and Network Meta-Analysis.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society Apr 1, 2026
BACKGROUND AND AIMS: Computer-aided detection (CADe) is anticipated to enhance adenoma detection rate (ADRs). The aim of this study was to systematically collect randomized-controlled trials comparing colonoscopy with CADe to standard colonoscopy wit... read more 

LCPBert: ProtBERT-based early-stage lung cancer prediction from T cell receptor beta sequences.

iScience Apr 1, 2026
Early detection of lung cancer remains challenging due to limitations of current methods. We developed LCPBert, a deep learning framework leveraging peripheral blood T cell receptor beta (TCRβ) repertoires for early detection of lung cancer. LCPBert ... read more 

SCAR-Net-assisted ultrasound diagnosis of postoperative scars and recurrent lesions in breast cancer.

iScience Apr 1, 2026
Postoperative differentiation between scar tissue and recurrent lesions in patients with breast cancer presents a significant diagnostic challenge. This study introduces SCAR-Net, a deep learning model specifically designed for ultrasound-based discr... read more 

Complex biological systems analysis and deep learning for prognostic prediction of esophageal squamous cell carcinoma.

iScience Apr 1, 2026
Esophageal squamous cell carcinoma (ESCC) prognosis remains poor, and traditional models often fail to capture complex nonlinear interactions between clinical and molecular features. We integrated transcriptomic data from public datasets and an indep... read more 

Towards robust deep reinforcement learning-based quantitative trading with neuro-symbolic trend analysis.

Neural networks : the official journal of the International Neural Network Society Apr 1, 2026
Deep reinforcement learning (DRL) has revolutionized quantitative trading (Q-trading) by achieving decent performance without significant human expert knowledge. Despite its achievements, we observe that the current state-of-the-art DRL models are st... read more 

Biochemical biomarker-Driven deep learning framework with SHAP-based feature interpretation for diabetes classification.

Biophysical chemistry Apr 1, 2026
Diabetes mellitus is a long-term metabolic condition that develops when the body cannot produce insulin effectively or use it properly. Individuals usually progress through a clinical spectrum that begins with normal glucose regulation, moves into a ... read more 

Exploration of an admittance control method for multi-segment spinal motion loading.

Clinical biomechanics (Bristol, Avon) Apr 1, 2026
BACKGROUND: In vitro testing is a fundamental approach for advancing spinal biomechanics research. However, existing loading methods still exhibit notable limitations in physiological realism and motion controllability. This study introduces a spinal... read more 

Characterization of suspended organic, inorganic, and microbial particles in water environment using an Electrical Sensing Zone (ESZ) method.

Talanta Apr 1, 2026
In aquatic environments, diverse particulate matter-including inorganic particles, organic particles, and microorganisms-significantly impacts water quality and ecological health. However, existing particle measurement technologies lack the capabilit... read more 

Harmonization in magnetic resonance imaging: A survey of acquisition, image-level, and feature-level methods.

Medical image analysis Apr 1, 2026
Magnetic resonance imaging (MRI) has greatly advanced neuroscience research and clinical diagnostics. However, imaging data collected across different scanners, acquisition protocols, or imaging sites often exhibit substantial heterogeneity, known as... read more 

Benchmarking text encoding strategies in multimodal clinical data for surgical case duration prediction.

International journal of medical informatics Apr 1, 2026
BACKGROUND: Operating rooms (ORs) are highly resource-intensive, yet surgical case duration is often estimated using heuristics that are prone to errors. While machine learning models based on structured perioperative data improve accuracy, unstructu... read more 
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