AI Medical Compendium

Unveiling the fate of heavy metals along the soil-rice-human pathway: Source-sink quantification, rhizospheric processes, and health implications.

Journal of hazardous materials Jan 15, 2026

Rapid industrial and agricultural intensification is increasing multi-source heavy metals (HMs) inputs into farmland, escalating risks to soil-crop system safety and human health. Limited source-sink flux data and inaccurate exposure estimates hinder... read more

Ultrasound measurements and normal values of the liver: a comprehensive review and practical guide.

Medical ultrasonography Jan 15, 2026

Reliable and reproducible sonographic measurements are essential for accurate liver assessment, both in daily clinical practice and in research. Reference values enable clinicians to differentiate between physiological and pathological findings and t... read more

GSR-ST: A generalized spatial-temporal framework for genomic signals and regions prediction using multi-scale feature fusion.

Computational biology and chemistry Jan 15, 2026

Genomic DNA sequences contain diverse functional genomic signals and regions (GSRs) that are crucial for regulating gene expression. The precise identification of these GSRs is fundamental to elucidating genomic architecture and understanding regulat... read more

Biometric Data in Post-Traumatic Stress Disorder Detection: A Scoping Review of Digital Health Applications.

International journal of medical informatics Jan 15, 2026

CONTEXT: Post-traumatic stress disorder (PTSD) is mainly assessed through self-reports and clinician interviews, which can delay recognition and limit reach. Biometric markers captured using digital technologies may enable earlier and more objective ... read more

Comment on "Early warning of harmful cyanobacteria blooms based on high frequency in situ monitoring and intelligible machine learning modelling: The case study of Lake Müggelsee (Germany)" by Recknagel et al. (Water Research 287 2025 124,514).

Water research Jan 15, 2026

Recknagel et al. (2025) present a timely study leveraging high-frequency in-situ data and three fundamentally different machine learning algorithms to forecast cyanobacterial blooms in Lake Müggelsee at a 5-day horizon. However, we note that four met... read more

Construction of a classification system for long-term care service needs among the elderly based on cluster analysis and machine learning: A multi-center, cross-sectional study in central China.

International journal of nursing studies Jan 15, 2026

BACKGROUND: Rapid global aging has led to an increasing demand for long-term care services for the elderly; however, current long-term care systems are underdeveloped and under-resourced. It is essential to develop an effective classification system ... read more

Predicting upwelling dynamics in the South Sea of Java, Indonesia: A deep learning approach with ConvLSTM and 3D-CNN.

MethodsX Jan 15, 2026

Oceans exhibit complex dynamics influenced by climate change, anthropogenic activities, and natural phenomena. Understanding these dynamics is critical for ensuring the sustainability of marine environments and their optimal utilization. This researc... read more

A multi-angle reflectance dataset of wheat and peach trees with unmanned aerial vehicle imagery.

Data in brief Jan 15, 2026

Medium- to high-resolution satellite data, such as Sentinel-2 and Landsat-8, have significantly enhanced the accuracy of vegetation monitoring. However, canopy reflectance and vegetation indices are affected by the bidirectional reflectance distribut... read more

ACFSENet: an adaptive cross-frequency global sparse encoding network for end-to-end EEG emotion recognition.

Biomedical physics & engineering express Jan 15, 2026

End-to-end EEG-based emotion recognition is attracting increasing attention due to its potential in human-computer interaction, mental health, and affective brain-computer interfaces (aBCIs). However, most existing methods overlook cross-frequency in... read more

Humans Neural Networks, Computer Algorithms Brain Emotions Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces

Explainable AI for pain perception: subject-independent EEG decoding using DeepSHAP and CNNs.