AI Medical Compendium

Explainable machine learning for the prediction of Alzheimer's disease-related cognitive impairment: a consensus feature selection approach.

BMC medical informatics and decision making May 29, 2026

BACKGROUND: Early identification of Alzheimer's disease-related cognitive impairment remains challenging, and existing machine learning (ML) models often suffer from feature instability and limited interpretability. This study developed robust and ex... read more

Why are rural hospitals closing in the U.S.? Predictors identified using explainable machine learning.

BMC health services research May 29, 2026

OBJECTIVE: Rural hospital closures in the U.S. reduce access to essential healthcare services and worsen health and economic outcomes in rural communities. This study uses national longitudinal data and explainable machine learning (XML) to identify ... read more

Toward equitable digital health: an integrated framework addressing exclusion, ethics, and implementation across healthcare systems.

International journal for equity in health May 29, 2026

BACKGROUND: Digital health technologies are fundamentally reshaping healthcare delivery, access, and governance worldwide. While these innovations offer unprecedented opportunities to extend services, particularly in resource-constrained settings, ea... read more

A survey of deep learning techniques in detecting neurological disorders using MRI.

Biomedical engineering online May 29, 2026

Magnetic resonance imaging (MRI) is widely regarded as the most reliable non-invasive imaging modality for detecting neurological disorders. However, manual interpretation of MRI scans is often time-consuming and prone to inter-observer variability, ... read more

Machine learning models for early mortality prediction in trauma patients using public data: a nationwide retrospective study.

World journal of emergency surgery : WJES May 29, 2026

BACKGROUND: Trauma is a leading cause of morbidity and mortality worldwide, particularly in younger populations. Early identification of high-risk trauma patients is critical for timely interventions and improved outcomes. Although artificial intelli... read more

Network toxicology and bioinformatics reveal potential molecular links between cadmium exposure and pancreatic cancer.

BMC pharmacology & toxicology May 29, 2026

BACKGROUND: Environmental cadmium (Cd) pollution poses a severe threat to human health due to its strong bioaccumulation and high carcinogenicity. Although Cd exposure has been linked to various cancers, its specific role in pancreatic cancer (PC) re... read more

KRT6A derived from mesenchymal stem cells as a potential biomarker and therapeutic target for alopecia areata: insights from multi-omics analysis and experimental evidence.

Stem cell research & therapy May 29, 2026

BACKGROUND: Mesenchymal stem cells (MSCs) secretome have shown promise in the treatment of alopecia areata (AA). However, the key therapeutic genes remain unclear. This study aimed to identify potential critical therapeutic molecules using multi-omic... read more

Artificial intelligence-based models in predicting acute exacerbations and diagnosing pediatric asthma: a systematic review and meta-analysis.

BMC medical informatics and decision making May 29, 2026

PURPOSE: This systematic review and meta-analysis evaluated the performance of artificial intelligence (AI)-based models in diagnosing pediatric asthma and predicting acute asthma exacerbations. METHODS: A comprehensive literature search was conducte... read more

DNA damage response signature-based prognostic genes for intrahepatic cholangiocarcinoma: a combined analysis of machine learning and biological experiments.

Cancer cell international May 29, 2026

BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) is a highly aggressive subtype of primary liver cancer with insidious onset, early metastasis, and poor prognosis. DNA damage response (DDR) dysfunction is linked to ICC tumorigenesis, progression, an... read more

EEG biomarkers can predict early-stage Alzheimer's disease and correlate with intracerebral pathology: a multimodal machine learning study.

Alzheimer's research & therapy May 29, 2026

BACKGROUND: Early recognition of Alzheimer's disease (AD) is crucial for timely intervention and delaying disease progression. Electroencephalogram (EEG) technology provides a direct reflection of the brain's dynamic activity. However, the relationsh... read more

Artificial Intelligence Medical Compendium