Artificial Intelligence Medical Compendium

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

Showing 9,761 to 9,770 of 208,614 articles

Modeling the Language of Codons with Artificial Intelligence.

Annual review of biomedical data science
The messenger RNA (mRNA) sequence plays a central role in expressing functional proteins from genes. Species-specific nonuniform codon choices influence key processes, including mRNA stability, translation accuracy and efficiency, and cotranslational... read more 

Assessment of pre-trained deep learning models in the detection of metal artifacts in axial cone beam tomography slices.

Dento maxillo facial radiology
OBJECTIVES: This study aimed to evaluate the performance of three pre-trained deep learning models (ResNet50, MobileNetV2, and EfficientNetB0) in the detection of metal artefacts (MAs) in axial cone-beam computed tomography (CBCT) slices. METHODS: Tw... read more 

Evaluation of Commonly Utilized Artificial Intelligence Large Language Models in Optimizing Readability, Accuracy, and Comprehension of Orthopaedic Oncology Patient Educational Materials.

The Journal of the American Academy of Orthopaedic Surgeons
INTRODUCTION: Online patient educational materials (PEMs) have poor readability, limiting their intended purposes in improving patient comprehension of health topics. Orthopaedic oncology PEMs are particularly complex. Although ChatGPT has demonstrat... read more 

Ambiguity Detection in Medical Exams via Large Language Models: Retrospective Cross-Sectional Pilot Study.

JMIR medical education
BACKGROUND: Large language models (LLMs) have emerged as promising tools in medical education due to their ability to understand, generate, and reason with natural language. Their ability to simulate expert reasoning suggests a potential for supporti... read more 

Large Language Model-Generated Patient Instructions for Prescriptions in Primary Health Care: Preclinical Algorithm Validation.

Journal of medical Internet research
BACKGROUND: The application of generative artificial intelligence to simplify medication use instructions has the potential to enhance people's health by improving treatment adherence. OBJECTIVE: We evaluated the performance of large language models ... read more 

Exploring the Use of Artificial Intelligence and Wearable Technologies in the Context of Cardiovascular Prevention From Early Detection to Cardiac Recovery: Protocol for a Scoping Review.

JMIR research protocols
BACKGROUND: Cardiac rehabilitation is an evidence-based, multidisciplinary intervention integrating therapeutic exercise, patient education, nutritional counseling, optimized pharmacological management, and psychological support. It reduces cardiovas... read more 

Machine Learning-Based Survival Prediction Models for Young Patients With Gastric Cancer: Model Development and Validation Study.

JMIR cancer
BACKGROUND: Despite a global decline in the incidence of gastric cancer (GC), the number of cases diagnosed among younger individuals continues to increase. Several studies have been conducted to develop predictive models of mortality in patients wit... read more 

Generative AI's Impact on the Mental Health of Medical Students: Scenario Analysis.

JMIR medical education
BACKGROUND: Generative artificial intelligence (AI) is quickly changing medical education, even as medical students still face high levels of stress, anxiety, and burnout. These simultaneous trends-technological upheaval and ongoing mental health iss... read more 

Survival prediction modeling for 1-year mortality in patients with ST elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI).

Heart & lung : the journal of critical care
BACKGROUND: ST elevation myocardial infarction (STEMI) is a life-threatening condition, and is associated with significant mortality, especially in patients encountering cardiogenic shock. Accurate risk assessment in this population is essential for ... read more 

From filtering to denoising: Increasing visual interpretability of cryo-electron tomograms.

Current opinion in structural biology
Cryo-electron tomography has emerged as the premier technique for ultrastructural analysis of natively preserved biological specimens and in situ structure determination. Each tomogram of a cell contains valuable information on the imaged molecular a... read more