AI Medical Compendium

Development and internal validation of machine learning in predicting prognosis of acute kidney injury patients in resource-limited setting.

Journal of critical care Feb 7, 2026

BACKGROUND: Machine learning models for predicting acute kidney injury (AKI) prognosis have primarily been developed in resource-rich settings, with limited validation in resource-limited environments. This study applied machine learning techniques t... read more

Current perspectives in cardiogenic shock.

Journal of critical care Feb 7, 2026

Cardiogenic shock (CS) remains a leading cause of death in intensive cardiac care. Outcomes are limited by delayed recognition of hypoperfusion, heterogeneous phenotypes, and late escalation of therapies. Diagnosis and risk stratification have progre... read more

Interaction between radon progeny and particulate matter in an urban environment.

Journal of environmental radioactivity Feb 7, 2026

Atmospheric radon progeny and particulate matter (PM) pose significant environmental health risks, yet their interactions and co-variability remain poorly quantified. This study investigates the interplay between short-lived outdoor radon progeny and... read more

Emergent Language Symbolic Autoencoder (ELSA) with weak supervision to model hierarchical brain networks.

Computers in biology and medicine Feb 7, 2026

Brain networks display hierarchical organization, a complexity that is challenging for deep learning models that are often flat classifiers and lack interpretability. To address this, we propose a novel architecture called the Emergent Language Symbo... read more

CT- DImQ: An open-access platform for image quality assessment of CT systems- application to CT values and noise characterization in 3D-printed anthropomorphic thorax phantoms.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Feb 7, 2026

PURPOSE: To present an open access platform for CT image quality assessment combined with anthropomorphic phantoms. To promote the accessibility of anthropomorphic phantoms, including 3D-printed affordable ones, in regular QC analysis of CT images re... read more

Simultaneous multimodal detection of hand acupoints and reflex zones for acupuncture robots.

iScience Feb 7, 2026

Acupuncture, a cornerstone of traditional Chinese medicine (TCM), faces challenges in standardization and precision, as its efficacy heavily relies on practitioner expertise. To address this, we propose a multimodal, multitask deep learning framework... read more

CGLK-GNN : A connectome generation network with large kernels for GNN based Alzheimer's disease analysis.

Neural networks : the official journal of the International Neural Network Society Feb 7, 2026

Alzheimer's disease (AD) is a currently incurable neurodegenerative disease, with early detection representing a high research priority. AD is characterized by progressive cognitive decline accompanied by alterations in brain functional connectivity.... read more

Physics-informed graph neural networks for flow field estimation in carotid arteries.

Medical image analysis Feb 7, 2026

Hemodynamic quantities are valuable biomedical risk factors for cardiovascular pathology such as atherosclerosis. Non-invasive, in-vivo measurement of these quantities can only be performed using a select number of modalities that are not widely avai... read more

BackTracker: Machine learning to identify kinematic phenotypes for personalised exercise management in non-specific low back pain.

International journal of medical informatics Feb 7, 2026

BACKGROUND: Low back pain (LBP) is a leading cause of global disability. Most cases are non-specific (NSLBP) and lack identifiable causes. Early active management is endorsed by clinical guidelines; however, exercises are rarely customised despite su... read more

Few-shot molecular property optimization via a domain-specialized large language model.

Chemical science Feb 7, 2026

Large language models (LLMs) have revolutionized machine learning with their few-shot learning and reasoning capabilities, demonstrating impressive results in fields like natural language processing and computer vision. However, when applied to the d... read more

Artificial Intelligence Medical Compendium