AI Medical Compendium

Interpretable machine learning using CT radiomics predicts pathological upgrading after secondary resection in non-muscle-invasive bladder cancer.

BMC cancer Jan 19, 2026

BACKGROUND AND PURPOSE: Repeat transurethral resection (ReTUR) is essential for reducing residual and recurrent non-muscle-invasive bladder cancer (NMIBC). Pathological upstaging after ReTUR significantly influences prognosis. This study aimed to dev... read more

Roles of microorganisms in the flavor evolution of prepared aquatic foods: comprehensively understanding their metabolic mechanisms, quorum sensing, and innovative regulation strategies.

Critical reviews in food science and nutrition Jan 19, 2026

Prepared aquatic foods refer to ready to eat, heat, cook, and use aquatic products. These foods are gaining popularity as a result of consumer preference for their peculiar flavor. Flavor deterioration of prepared aquatic foods directly impacts the s... read more

Lesion stratification with intracoronary imaging.

EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology Jan 19, 2026

Intracoronary (IC) imaging-guided percutaneous coronary intervention (PCI) improves clinical outcomes in patients with high clinical and anatomical risk when compared to interventions guided by angiography alone. Recent Class I recommendations for th... read more

Humans Artificial Intelligence Coronary Angiography Percutaneous Coronary Intervention Coronary Artery Disease Coronary Vessels Plaque, Atherosclerotic

Development of an artificial intelligence-based algorithm for the detection of left atrial enlargement from feline thoracic radiographs.

The veterinary quarterly Jan 19, 2026

A heart-convolutional neural network (heart-CNN) was developed and tested for the automatic detection of left atrial enlargement (LAE) from feline thoracic radiographs. A retrospective and multicenter study was performed. Right lateral and dorso-vent... read more

Neural Networks, Computer Artificial Intelligence Algorithms Retrospective Studies Female Animals Male Echocardiography Cardiomegaly Heart Atria Cats Cat Diseases Radiography, Thoracic

The most vulnerable are prone to use AI therapists: The role of attachment, epistemic trust, and mental health symptoms in acceptance of digital mental health interventions.

Psychotherapy research : journal of the Society for Psychotherapy Research Jan 19, 2026

OBJECTIVE: Digital mental health interventions (DMHIs) offer scalable solutions to traditional barriers in mental healthcare. Acceptability of DMHIs might differ among patients with differing level of symptoms and relational difficulties. This study ... read more

Machine Learning-Driven Nanopore Sensing for Quantitative, Label-Free miRNA Detection.

Small methods Jan 19, 2026

Nanopore sensors offer exceptional sensitivity for detecting single molecules, making them ideal for early disease diagnostics. In this study, we present a multiplexed nanopore-based assay that combines DNA-barcoded probes with advanced computational... read more

Deep learning in stroke therapeutics: drug repurposing and beyond.

Expert opinion on drug discovery Jan 19, 2026

INTRODUCTION: Deep learning is reshaping stroke research by accelerating drug repurposing amid heterogeneous pathology, narrow therapeutic windows, and poor translation. This review highlights current therapeutic challenges and emerging DL applicatio... read more

Development of Betalactam-Predictor: A Clinical Decision Tool for Delabeling Low-Risk Betalactam Allergy Patients. Initial Validation in Penicillin Allergy.

Allergy Jan 19, 2026

BACKGROUND: A label of betalactam (BL) allergy is estimated in around 10% of the population in their medical records. Second-line choices carry significant negative consequences, including reduced efficacy, effectiveness, and safety. This study aimed... read more

The Potential of Ensemble-Based Automated Sleep Staging on Single-Channel EEG Signal From a Wearable Device.

Journal of sleep research Jan 19, 2026

Machine-learning-based sleep staging models have achieved expert-level performance on standard polysomnographic (PSG) data. However, their application to EEG recorded by wearable devices remains limited by non-conventional referencing montage and the... read more

Artificial intelligence for schizophrenia: from unimodal prediction to multimodal characterization.

Current opinion in psychiatry Jan 19, 2026

PURPOSE OF REVIEW: Artificial intelligence is increasingly advancing both fundamental research and clinical applications in schizophrenia. This review surveys recent literature on artificial intelligence driven approaches for schizophrenia diagnosis,... read more

Artificial Intelligence Medical Compendium