AI Medical Compendium

Advances and innovations in machine learning-based spectral detection methods for trace organic pollutants.

The Analyst Jan 19, 2026

The rapid and sensitive detection of trace organic pollutants in water is crucial for ensuring environmental safety. Traditional detection methods struggle to meet the demands of large-scale, real-time, and on-site detection. This paper reviews recen... read more

Progress of lateral flow assays for the detection of molecular and microbial species: from basic formats to microfluids, CRISPR and artificial intelligence.

The Analyst Jan 19, 2026

Lateral flow assays (LFAs) have garnered much interest in the biomedical and agricultural sciences because of their user-friendly design, quick turnaround times, minimal interference, affordability, and ease of use by individuals. To date, many resea... read more

Humans Artificial Intelligence Bacteria

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

Case-based reasoning for clinical trial recruitment tools in oncology: When you need patients to find patients.

International journal of medical informatics Jan 19, 2026

BACKGROUND: Patient recruitment for clinical trials remains a major challenge, with 86% of trials failing to meet enrollment targets on time. In over 77% of cases, recruitment difficulties stem from matching problems between trials and patients. Case... read more

Towards sustainable management of Xylella fastidiosa vectors: An annotated image dataset for automated in-field detection of Aphrophoridae foam.

Data in brief Jan 19, 2026

Insects feeding on xylem sap, such as adult Aphrophoridae spittlebugs, are vectors of the plant pathogenic xylem-limited bacterium Xylella fastidiosa (Xf), a causal agent of a number of severe diseases, including the Olive Quick Decline Syndrome (OQD... read more

Coniferyl aldehyde in ginger-Eucommiae Cortex enhances osteoarthritis treatment by modulating ALDOA and H3K23la histone lactylation.

Phytomedicine : international journal of phytotherapy and phytopharmacology Jan 19, 2026

BACKGROUND AND PURPOSE: Eucommiae Cortex (EC), a traditional Chinese medicinal herb, has been utilized to treat osteoarthritis (OA). The therapeutic efficacy of EC can be augmented by combining it with ginger juice. OA is often linked to metabolic di... read more

Label-free Raman spectroscopy combined with artificial intelligence for functional subtyping of human sperm and prediction of embryo development outcomes.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jan 19, 2026

Raman spectroscopy delivers label-free, non-destructive, single-cell measurements and directly senses intrinsic biochemical signals of nucleic acids, proteins, and lipids. Conventional semen analysis offers limited prognostic power for assisted repro... read more

Development of prediction models for perioperative opioid needs in laparoscopic cholecystectomy patients: A machine-learning approach.

Surgery open science Jan 19, 2026

BACKGROUND: Changes in opioid prescribing practices have evolved, including perioperative settings. However, computerized clinical decision support systems to guide opioid prescribing remain limited. This study aimed to develop and validate predictio... read more

MCDNet: Morphological-conditional dual-view fusion for 3D tubular structure segmentation.

Neural networks : the official journal of the International Neural Network Society Jan 19, 2026

Accurate segmentation of 3D tubular structures in medical images is critical for clinical diagnosis and interventional planning. Although deep learning methods have advanced significantly, most existing approaches exhibit limited generalizability due... read more

Machine Learning Prediction of Chronic Kidney Disease in Elderly MetS Patients Using NHANES 2011-2020 Data.

Rejuvenation research Jan 19, 2026

BACKGROUND: Chronic kidney disease (CKD) is getting more common in elderly people with metabolic syndrome, but early detection and risk prediction are still hard. So we created and validated a CKD risk prediction model tailored for these patients to ... read more

Artificial Intelligence Medical Compendium