AI Medical Compendium

Deep learning-based cervical cancer T-staging using MRI: multi-structure segmentation and classification.

BMC medical imaging May 30, 2026

AIMS: Cervical cancer has high incidence and mortality, seriously threatening women's survival and quality of life. Radiologists currently rely mainly on subjective clinical experience for cervical cancer T-staging, which easily leads to misdiagnosis... read more

Electronic health record-derived machine learning model for hypoglycemia risk prediction in type 2 diabetes mellitus patients: development and validation.

BMC endocrine disorders May 30, 2026

BACKGROUND: Hypoglycemia is a serious complication of diabetes. Early recognition of hypoglycemia can improve clinical prognosis, however, traditional diagnostic tools are often limited. Machine learning offers a promising approach for predicting adv... read more

Care ethics and the transformation of care in an age of artificial intelligence.

BMC medical ethics May 30, 2026

BACKGROUND: The integration of artificial intelligence (AI) and care robots into healthcare raises a central ethical question: what constitutes care, and how should it be delivered when machines perform caregiving tasks? Dominant AI ethics frameworks... read more

Machine learning-based prediction of intellectual disability in children with autism spectrum disorder: using behavioral observation techniques.

BMC psychiatry May 30, 2026

PURPOSE: To construct and evaluate a LightGBM prediction model for intellectual disabilities in children with Autism Spectrum Disorder (ASD). METHODS: A total of 384 ASD children who completed the Wechsler Intelligence Test and Adaptive Behavioral As... read more

Extracellular vesicle and particle biomarkers in cancer: a machine learning blueprint for liquid biopsy.

Journal of nanobiotechnology May 30, 2026

The combination of machine learning and liquid biopsy is rapidly promoting the development of precision cancer diagnosis. Extracellular vesicles and particles (EVPs) are liquid biopsy markers with great diagnostic value due to their unique structure,... read more

Artificial intelligence-assisted feedback in pharmacology education: a pilot evaluation of a custom generative model.

BMC medical education May 30, 2026

BACKGROUND: Timely, individualised feedback is central to effective learning in medical education but remains resource intensive, particularly when based on short answer questions (SAQs). Large language models (LLMs) offer potential to support feedba... read more

Use of virtual reality simulation in preparation for practical training in healthcare education - a mixed method study with students and educators.

BMC medical education May 30, 2026

INTRODUCTION: Simulation-based education promotes active learning and reflective practice in healthcare education. With the advancement of immersive technologies, virtual reality (VR) enables simulation of complex clinical interactions in a safe and ... read more

Development and external validation of multiple machine learning-based models for breast cancer-specific survival prediction in postoperative patients with invasive breast cancer: a study based on the SEER database and an external cohort.

BMC cancer May 30, 2026

BACKGROUND: Patients with invasive breast cancer (IBC) account for the vast majority of breast cancer cases and exhibit significant heterogeneity; hence, it is necessary to develop a model that can accurately predict their long-term postoperative bre... read more

Machine learning prediction of long-term postoperative pneumonia risk: a retrospective cohort study.

BMC medical informatics and decision making May 30, 2026

BACKGROUND: Postoperative pneumonia is a significant complication, highlighting a patient's ongoing vulnerability. While traditional tools focus on short-term outcomes, the perioperative period offers a unique "stress test" window to identify high-ri... read more

Organoids as next-generation models for investigating intracranial tumours.

Molecular brain May 30, 2026

Tumour organoids have emerged as important tools in brain tumour research, addressing long-standing limitations of conventional two-dimensional cultures, xenograft models, and genetically engineered mouse models. By preserving patient-specific geneti... read more

Artificial Intelligence Medical Compendium