AI Medical Compendium

Investigating the associations between AI-Based educational tool utilization, academic procrastination, academic achievement, and time management among nursing students.

BMC nursing May 29, 2026

BACKGROUND: The role of artificial intelligence (AI) tools in education has transformed the way students learn and manage their academic tasks. However, health professions education has not sufficiently studied the role of AI tools in procrastination... read more

A two-stage sperm holomorphological analysis method based on multi-output network construction.

BMC bioinformatics May 29, 2026

BACKGROUND: Sperm morphology detection technology has important research value in diagnosing male infertility. Traditional manual detection methods are time-consuming, labor-intensive, and highly subjective. The sperm morphology analysis method based... read more

Decoding the role of H19 in cholestatic liver injury using snRNA-seq, spatial transcriptomics, and machine learning-based disease prediction.

Cell & bioscience May 29, 2026

BACKGROUND: Despite recent advances, Primary Sclerosing Cholangitis (PSC)-a chronic obstructive biliary disease-still lacks effective therapies to prevent disease progression or the need for liver transplantation. Moreover, up to 30% of transplant re... 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

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

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

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

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

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

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

Artificial Intelligence Medical Compendium