AI Medical Compendium

Predicting neoadjuvant immunotherapy efficacy with machine learning models in non-small cell lung cancer: A systematic review and meta analysis.

International journal of medical informatics Feb 13, 2026

BACKGROUND: The response of resectable non-small cell lung cancer (NSCLC) to neoadjuvant immunotherapy is heterogeneous. Machine learning can integrate multimodal data to construct predictive models, but the methodological quality, risk of bias and c... read more

Identification and experimental confirmation of TBC1D10C as a shared transcriptional link between abdominal aortic aneurysm and major depressive disorder.

Biochemical and biophysical research communications Feb 13, 2026

BACKGROUND: Abdominal aortic aneurysm (AAA) and major depressive disorder (MDD) are prevalent conditions with substantial global health burdens. Growing clinical evidence indicates a close relationship between them, implicating shared pathogenic mech... read more

Enhancing breast cancer diagnostics: Shape-aware angular feature learning for precision in breast cancer classification.

Computational biology and chemistry Feb 13, 2026

Breast cancer is a life-threatening disease that is very common among women in the world. The early and correct diagnosis is necessary to enhance the rate of survival and treatment. The conventional techniques such as mammography, ultrasound and MRI ... read more

Interpretable prognostic modeling of glioblastoma using cross-cohort transcriptome integration and machine learning approaches.

Biochemical and biophysical research communications Feb 13, 2026

Glioblastoma (GBM) is an aggressive brain tumor with highly variable patient outcomes due to pronounced molecular heterogeneity. Prognosis remains dismal (median survival ∼15 months) and current prognostic models often function as "black boxes," lack... read more

FreqMLNet: Non-transformer network with frequency domain reconstruction and multi-scale representation for time series forecasting.

Neural networks : the official journal of the International Neural Network Society Feb 13, 2026

Time series forecasting is essential in finance, meteorology, healthcare, and industrial process control. Traditional time-domain forecasting methods struggle to capture complex patterns and structures. Frequency-domain analysis offers an alternative... read more

Automated prescription of therapeutic exercise for shoulder impingement syndrome using literature-driven rule generation architecture.

Musculoskeletal science & practice Feb 13, 2026

BACKGROUND: Shoulder impingement syndrome (SIS) is a common musculoskeletal disorder that requires individualized therapeutic exercise prescription. However, it is challenging to provide individualized prescriptions based on the latest evidence. OBJE... read more

Late distant recurrence prediction model in premenopausal women with ER-positive/HER 2-negative breast cancer: A multicenter retrospective study.

Breast (Edinburgh, Scotland) Feb 13, 2026

BACKGROUND: Late distant recurrence (DR) remains a significant challenge in estrogen receptor (ER)-positive/Human Epidermal Growth Factor Receptor 2 (HER2)-negative breast cancer, especially in premenopausal patients. This study aimed to develop a ma... read more

Maintaining patient trust as artificial intelligence's role in healthcare grows.

The New Zealand medical journal Feb 13, 2026

Patient trust is key to the delivery of healthcare and realisation of artificial intelligence's (AI) benefits in health. Trust in health institutions and the health professionals working within them directly impacts patient engagement with health ser... read more

Development and explanation of electrocardiogram-based deep learning for predicting short-term mortality in heart failure patients.

Journal of global health Feb 13, 2026

BACKGROUND: Heart failure mortality has risen sharply after years of decline, highlighting the limitations of current risk assessment tools in accuracy, complexity, and cost, and the need for improved predictive models. To address this gap, we develo... read more

Predicting the need for electroconvulsive therapy via machine learning trained on electronic health record data.

Acta neuropsychiatrica Feb 13, 2026

OBJECTIVES: Electroconvulsive therapy (ECT) is an effective treatment of severe manifestations of mental illness. Since delay in initiation of ECT can have detrimental effects, prediction of the need for ECT could improve outcomes via more timely tre... read more

Artificial Intelligence Medical Compendium