Latest AI in Medicine Research | AI Medical Compendium

Beyond Fine-Tuning: Leveraging Domain-Aware In-Context learning with large language models for clinical named entity recognition.

Journal of biomedical informatics Jan 8, 2026

BACKGROUND: Clinical named entity recognition (NER) is essential for structuring clinical narratives. While large language model (LLM)-based in-context learning (ICL) enables parameter-free adaptation, encoder-based fine-tuning has generally achieved... read more

Expansion of CKD diagnostics through biosensor technology: An early detection approach.

Clinica chimica acta; international journal of clinical chemistry Jan 8, 2026

Chronic kidney disease (CKD) is a complicated global health disease that causes serious health issues like kidney failure and heart-related problems. These complications make the conditions worse for the patients and also increase the mortality rate ... read more

Seasonally adaptive data-driven ozone prediction in megacity environments.

Environmental research Jan 8, 2026

Ground level ozone (O3) concentrations have shown a persistent upward trend in urban megacities over the past decade, despite substantial reductions in primary pollutant emissions through regulatory and technological interventions. Unlike primary pol... read more

Machine learning-driven water quality index prediction in the Dau Tieng reservoir, southern Vietnam, with interpretability via SHapley additive exPlanations: A vision for water quality management strategies.

Environmental research Jan 8, 2026

Freshwater reservoirs are essential for ecological stability, biodiversity preservation, and resource sustainability. Managing water quality effectively poses challenges due to complex environmental pressures and limitations in traditional monitoring... read more

Association between the insulin resistance indices and incident type 2 diabetes across different body mass index states: a cohort study and external validation from two East Asian populations.

Diabetes research and clinical practice Jan 8, 2026

BACKGROUND: Insulin resistance (IR) indices like the TyG index are predictors of type 2 diabetes (T2DM), but their comparative performance across BMI categories in East Asians is unclear. METHODS: This retrospective cohort study enrolled 114,293 Chin... read more

Multi-Architecture deep learning for CBCT segmentation of dental hard tissues and pulp in mixed dentition.

Journal of dentistry Jan 8, 2026

OBJECTIVE: To develop and evaluate deep learning-based 3D models (CNN, Transformer, and Mamba architectures) for automated segmentation of pulp, primary, and permanent dental structures in pediatric CBCT scans with mixed dentition. METHODS: A total o... read more

A multi-layer hypergraph framework for drug-drug interaction prediction based on transformer and hypergraph convolution.

Computational biology and chemistry Jan 8, 2026

Drug-drug interactions represent a key problem for drug research, development, and clinical practice. It is crucial to accurately predict interactions when drugs combine to improve treatment safety and optimize medication regimens. However, the expon... read more

Temporal local attention with adaptive decoding: Enhancing spiking neural networks for temporal computing applications.

Neural networks : the official journal of the International Neural Network Society Jan 8, 2026

The brain-inspired spiking neural networks (SNNs) are considered to have great potential in complex learning due to their rich neural dynamics and high energy efficiency. Their unique mechanisms are naturally suited for performing temporal computing ... read more

A novel backpropagation algorithm based on negated kurtosis loss for training shallow, convolutional, and deep neural networks.

Neural networks : the official journal of the International Neural Network Society Jan 8, 2026

The conventional backpropagation (BP) algorithm remains the most widely used approach for training neural networks (NNs), including shallow NN (SNN), convolutional NN (CNN), deep NN (DNN), and deep CNN (DCNN), due to its easy implementation and well-... read more

Identification potential of cognitive-motor dual-task gait in frailty via machine learning model.

Gait & posture Jan 8, 2026

BACKGROUND: The early diagnosis and intervention of frailty play a crucial role in enhancing the quality of life for elderly individuals in their later years. Currently, the identification of frailty relies on various manual assessment scales, which ... read more

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