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

Early management of acute heart failure.

Current opinion in critical care Jan 19, 2026

PURPOSE OF REVIEW: Acute heart failure (AHF) is a frequent, high-risk emergency department presentation in which early diagnostic and therapeutic decisions strongly influence outcomes. This review is timely as new evidence is reshaping the first hour... read more

Data-driven assessment of nitrogen and phosphorus buffering capacity across 460 Chinese watersheds: Spatial patterns, drivers, and future projections.

Water research Jan 19, 2026

Watershed nitrogen and phosphorus buffering capacity refers to the capacity of a watershed to retain nitrogen and phosphorus in soil, groundwater, and sediments, playing an important regulatory role in balancing human-induced nutrient inputs with dow... read more

TSMS-SAM2: Multi-scale Temporal Sampling Augmentation and Memory-Splitting Pruning for Promptable Video Object Segmentation and Tracking in Surgical Scenarios.

Machine learning. Health Jan 19, 2026

Promptable video object segmentation and tracking (VOST) has seen significant advances with the emergence of foundation models like Segment Anything Model 2 (SAM2); however, their application in surgical video analysis remains challenging due to comp... read more

SCAD: A self-constrained solution to automate context-guided zero-shot image anomaly detection.

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

Image anomaly detection (IAD) usually requires a separated train set to build an inductive model, which then infers on the test set. However, the cost of collecting and labeling training images has inspired zero-shot IAD (ZS-IAD), which directly proc... read more

Empowering front-line physicians with AI: Evaluating large language models in everyday ENT care.

The American journal of emergency medicine Jan 19, 2026

PURPOSE: Artificial intelligence systems known as large language models are being evaluated for clinical decision support, yet their role in emergency and primary care remains limited. Physicians in these settings often encounter ear, nose, and throa... read more

Developing a trustworthy and explainable framework for classifying skin lesions through transfer learning and attention mechanisms.

Computational biology and chemistry Jan 19, 2026

Detection of high precision skin lesions, especially melanoma, are still a major challenge in medical imagination due to their close visual equality and lack of reliably labeled datasets. In this study, we introduce a deep learning sketch aimed at ba... read more

Interface-engineered Gd₂O₃/ZrO₂ bilayer memristor for emulating synaptic plasticity in neuromorphic systems.

Journal of colloid and interface science Jan 19, 2026

Rare-earth-based materials are attracting growing interest for neuromorphic devices due to their unique electronic structures, defect engineering capabilities, and high ionic mobility, which enable energy-efficient and highly controllable memristive ... read more

UniTrain: A universal iterative semi-supervised training framework for graph representation learning.