Artificial Intelligence Medical Compendium

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

Showing 34,311 to 34,320 of 221,510 articles

Reduced spread of nodes in spatial network models improves topology associated with increased computational capabilities

bioRxiv Apr 5, 2026
Biological neural networks are characterized by short average path lengths, high clustering, and modular and hierarchical architectures. These complex network topologies strike a balance between local specialization and global synchronization via lon... read more 
neuroscience

CellBench-LS: Benchmark Evaluation of Single-cell Foundation Models for Low-supervision Scenarios

bioRxiv Apr 5, 2026
While single-cell foundation models (SCFMs) have shown promise across various downstream tasks, their generalization performance in label-scarce settings remains a critical bottleneck. The absence of systematic benchmarks for these low-resource scena... read more 
cell biology

OpenAc4C: A gateway to decode the landscape, regulation and pathogenesis of N4-acetylcytidine (ac4C) epitranscriptome

bioRxiv Apr 5, 2026
N4-acetylcytidine (ac4C) is an ancient and highly conserved chemical marker found in all domains of life. Recent advancements in sequencing techniques have enabled the functional analysis of ac4C occurrence by accurately capturing its locations and l... read more 
bioinformatics

Interpretable Deep Learning-Based Multi-Omics Integrationfor Prognosis in Hepatocellular Carcinoma

bioRxiv Apr 5, 2026
Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality worldwide, yet existing prognostic models incompletely capture its molecular heterogeneity. We developed an interpretable, attention-based multi-branch deep learning framework for ... read more 
bioinformatics

Machine learning-driven prognostication in liver transplantation: A tacrolimus intrapatient variability enhanced predictive model.

Hepatobiliary & pancreatic diseases international : HBPD INT Apr 5, 2026
BACKGROUND: Accurately predicting long-term survival after liver transplantation (LT) remains a major clinical challenge. Tacrolimus intrapatient variability (Tac-IPV) has emerged as a potential prognostic marker, yet its integration into clinical de... read more 

Automated detection of tooth loss using tooth numbering segmentation in 3D intraoral scans from a population-based sample with artificial intelligence.

Journal of dentistry Apr 5, 2026
OBJECTIVES: This study aimed to validate an automated method for detecting tooth loss in intraoral scans (IOS) compared to clinical evaluations in a population-based sample. METHODS: 897 IOSs from 453 participants of the 1982 Pelotas Birth Cohort wer... read more 

Beyond exam accuracy: Tracking a persistent-failure set reveals visual dental reasoning gaps in multimodal LLMs.

Journal of dentistry Apr 5, 2026
OBJECTIVES: To benchmark late-2025 general-purpose multimodal large language models (LLMs) on the Japanese National Dental Examination (JNDE) and to reassess a previously identified persistent-failure set. METHODS: GPT-5.2T, Claude 4.5, and Gemini 3 ... read more 

High-resolution LA-ICP-MS imaging combined with attention-enhanced residual network reveal cadmium-induced metal distribution heterogeneity and toxicity in Mytilus galloprovincialis.

Journal of hazardous materials Apr 5, 2026
Marine bivalves often face heavy metal stress, yet we still lack of high-resolution way to observe the metal pollution status in soft tissue. This study provides the first high-resolution spatial mapping of cadmium (Cd) and associated heavy metals in... read more 

Digital health and machine learning in population health and wellness management: A scoping and bibliometric review of effectiveness, equity, and implementation challenges.

Asian journal of psychiatry Apr 5, 2026
Machine learning (ML) in digital health applications is becoming more popular for the general management of population wellness and the promotion of large-scale prevention, risk stratification, and the use of data to formulate data-driven decision-ma... read more 

An effluent risk informed closed-loop framework for early warning of influent anomalies using COD soft sensing.

Water research Apr 5, 2026
Sudden shock loads in wastewater influent can severely disrupt biological treatment processes and cause effluent quality exceedances in wastewater treatment plants, particularly in domestic-industrial integrated facilities. Timely and reliable early ... read more 
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