Latest AI in Medicine Research | AI Medical Compendium

GCLSC: Single-cell clustering model based on graph contrastive learning.

Computational biology and chemistry Jan 11, 2026

The advent of single-cell RNA sequencing (scRNA-seq) technology has enabled the analysis of cellular heterogeneity at the single-cell level. In scRNA-seq data analysis, cell clustering is a crucial downstream task, as it facilitates the discovery of ... read more

Sequential viseme-driven visual speech recognition through dual-stream interactive neural architecture.

Neural networks : the official journal of the International Neural Network Society Jan 11, 2026

While achieving considerable success as a sequence-to-sequence prediction task, current deep neural network-based sentence-level lipreading methods exhibit a fundamental limitation: the preservation of overall semantics often comes at the expense of ... read more

Shap-interpretable predictive modeling of microvascular invasion and early recurrence in hepatocellular carcinoma using MRI habitat imaging combined with clinical features.

European journal of radiology Jan 11, 2026

OBJECTIVE: To develop and validate an integrated model combining Gd-EOB-DTPA-enhanced MRI habitat imaging with clinical features for preoperative prediction of microvascular invasion (MVI) and early recurrence in hepatocellular carcinoma (HCC). METHO... read more

C2HFusion: Clinical context-driven hierarchical fusion of multimodal data for personalized and quantitative prognostic assessment in pancreatic cancer.

Medical image analysis Jan 11, 2026

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy. Accurate prognostic modeling enables reliable risk stratification to identify patients most likely to benefit from adjuvant therapy, thereby facilitating individualized clinic... read more

VENI, VINDy, VICI: A generative reduced-order modeling framework with uncertainty quantification.

Neural networks : the official journal of the International Neural Network Society Jan 11, 2026

Generative models are transforming science and engineering by enabling efficient synthetization and exploration of new scenarios for complex physical phenomena with minimal cost. Although they provide uncertainty-aware predictions to support decision... read more

Development of a new tool for prediction of hospital length of stay and intensive care needs in trauma patients using Machine Learning.

Injury Jan 10, 2026

BACKGROUND: Trauma is a major global health burden leading to significant morbidity, disability, and mortality. Predictive models in trauma care traditionally focus on mortality, but early predictions of hospital length of stay (LOS) and intensive ca... read more

Reconnecting new tetrahydrobenzothieno-4-pyrimidine amides as potent PIM-1 kinase inhibitors via an integrated ligand, machine learning model and structure based scaffold hopping: In vitro anti-tumor investigations.

Bioorganic chemistry Jan 10, 2026

PIM1 has been known to be one of the prolific molecular target in the discovery of new potential anticancer drugs due to its engagement in activation of cell proliferation and anti-apoptosis. Till date not a single drug is in the market that targets ... read more

Automated diagnosis of usual interstitial pneumonia on chest CT via the mean curvature of isophotes.

European journal of radiology open Jan 10, 2026

PURPOSE: To test whether the mean curvature of isophotes (MCI), a geometric image transformation, can be used to improve automatic detection on chest CT of Usual Interstitial Pneumonia (UIP), a determining radiological pattern in the diagnosis of Int... read more

Artificial intelligence in breast cancer screening: A systematic review and meta-analysis of integration strategies.

European journal of radiology open Jan 10, 2026

OBJECTIVE: To compare AI-augmented and conventional double reading in organised breast-cancer screening with respect to cancer-detection rate (CDR), recall rate, and radiologist workload. METHODS: We conducted a systematic review and random-effects m... read more

Mitigating data center bias in cancer classification: Transfer bias unlearning and feature size reduction via conflict-of-interest free multi-objective optimization.

Artificial intelligence in medicine Jan 10, 2026

Bias in the decision-making processes of trained deep models poses a significant threat to their reliability. Such bias can lead to overoptimistic results on observed data while compromising generalization to unseen datasets. Training data may contai... read more

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