Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 1,511 to 1,520 of 200,346 articles

Machine-learning prediction of 30-day infection-related hospitalization in advanced CKD.

BMC infectious diseases
BACKGROUND: Patients with advanced chronic kidney disease (CKD), defined as having an estimated glomerular filtration rate (eGFR) < 45 ml/min/1.73 m², are vulnerable to infections leading to hospitalization. Predicting such events using routine clini... read more 

DeepCas12a: a hybrid deep learning framework for accurate AsCas12a efficiency prediction from sequence and epigenetic information.

BMC genomics
CRISPR-Cas12a (Cpf1) offers distinct advantages for genome editing due to its flexible, T-rich PAM recognition. However, variable cleavage efficiency-modulated by sequence context and epigenetic features-remains a challenge, with existing tools facin... read more 

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

BMC medical imaging
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
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
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
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
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
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
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
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