AI Medical Compendium

EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning.

BMC bioinformatics Jan 24, 2026

BACKGROUND: DNA sequences are fundamental carriers of genetic information, and their accurate classification is essential for understanding gene regulation, disease mechanisms, and translational genomics. Existing encoding methods often fail to captu... read more

HDGS-Net: nucleosome occupancy prediction based on a hybrid dilated gated separable convolutional neural network.

BMC genomics Jan 24, 2026

Predictive associations between brain functional connectivity, motor abilities, and executive function development in early childhood: a longitudinal machine learning study.

Journal of neuroengineering and rehabilitation Jan 24, 2026

An online non-radiographic osteoporosis prediction calculator constructed using interpretable machine learning.

BioData mining Jan 24, 2026

Enhancing anesthesia monitoring training: a SPOC and Gagné's model hybrid personalized by artificial intelligence.

BMC medical education Jan 24, 2026

BACKGROUND: High-quality training in anesthesia nursing-particularly in intraoperative monitoring-is essential for ensuring patient safety. However, the rapid shift toward online learning after COVID-19 has led to challenges such as reduced interacti... read more

Artificial intelligence-based tumor-stroma ratio quantification reveals prognostic value and stromal-driven immunosuppression in colorectal cancer: an international validation study.

Journal of translational medicine Jan 24, 2026

Prognostic value of the triglyceride-glucose index combined with atherogenic index of plasma for all-cause mortality in critically ill patients with chronic heart failure: a machine learning-driven retrospective cohort study.

Lipids in health and disease Jan 24, 2026

BACKGROUND: The triglyceride-glucose index (TyG) and atherogenic index of plasma (AIP) are emerging metabolic biomarkers associated with cardiovascular diseases. However, their combination prognostic value in patients with critical chronic heart fail... read more

Construction of an interpretable machine learning model for predicting gestational diabetes mellitus based on 45 dietary nutrients.

BioData mining Jan 24, 2026

A deep ensemble encoder network method for improved polygenic risk score prediction.

BioData mining Jan 24, 2026

Single-cell sequencing analysis and machine learning model reveal aberrant TIM-3 expression in microglia during Alzheimer's disease progression.

Journal of translational medicine Jan 24, 2026

Artificial Intelligence Medical Compendium

EDEN: multiscale expected density of nucleotide encoding for enhanced DNA sequence classification with hybrid deep learning.

HDGS-Net: nucleosome occupancy prediction based on a hybrid dilated gated separable convolutional neural network.

Predictive associations between brain functional connectivity, motor abilities, and executive function development in early childhood: a longitudinal machine learning study.

An online non-radiographic osteoporosis prediction calculator constructed using interpretable machine learning.

Enhancing anesthesia monitoring training: a SPOC and Gagné's model hybrid personalized by artificial intelligence.

Artificial intelligence-based tumor-stroma ratio quantification reveals prognostic value and stromal-driven immunosuppression in colorectal cancer: an international validation study.

Prognostic value of the triglyceride-glucose index combined with atherogenic index of plasma for all-cause mortality in critically ill patients with chronic heart failure: a machine learning-driven retrospective cohort study.

Construction of an interpretable machine learning model for predicting gestational diabetes mellitus based on 45 dietary nutrients.

A deep ensemble encoder network method for improved polygenic risk score prediction.

Single-cell sequencing analysis and machine learning model reveal aberrant TIM-3 expression in microglia during Alzheimer's disease progression.

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