AI Medical Compendium Journal:
JMIR medical informatics

Showing 1 to 10 of 65 articles

Trajectory-Ordered Objectives for Self-Supervised Representation Learning of Temporal Healthcare Data Using Transformers: Model Development and Evaluation Study.

JMIR medical informatics
BACKGROUND: The growing availability of electronic health records (EHRs) presents an opportunity to enhance patient care by uncovering hidden health risks and improving informed decisions through advanced deep learning methods. However, modeling EHR ...

Enhancing Antidiabetic Drug Selection Using Transformers: Machine-Learning Model Development.

JMIR medical informatics
BACKGROUND: Diabetes affects millions worldwide. Primary care physicians provide a significant portion of care, and they often struggle with selecting appropriate medications.

Intelligent Prediction Platform for Sepsis Risk Based on Real-Time Dynamic Temporal Features: Design Study.

JMIR medical informatics
BACKGROUND: The development of sepsis in the intensive care unit (ICU) is rapid, the golden rescue time is short, and the effective way to reduce mortality is rapid diagnosis and early warning. Therefore, real-time prediction models play a key role i...

Machine Learning and Deep Learning Techniques for Prediction and Diagnosis of Leptospirosis: Systematic Literature Review.

JMIR medical informatics
BACKGROUND: Leptospirosis, a zoonotic disease caused by Leptospira bacteria, continues to pose significant public health risks, particularly in tropical and subtropical regions.

Machine Learning for the Prediction of Acute Kidney Injury in Critically Ill Patients With Coronary Heart Disease: Algorithm Development and Validation.

JMIR medical informatics
BACKGROUND: Acute kidney injury (AKI) frequently occurs in critically ill patients with coronary heart disease (CHD), and its development markedly elevates mortality rates and prolongs hospitalization duration. Early AKI prediction is crucial for tim...

Prediction of Spontaneous Breathing Trial Outcome in Critically Ill-Ventilated Patients Using Deep Learning: Development and Verification Study.

JMIR medical informatics
BACKGROUND: Long-term ventilator-dependent patients often face problems such as decreased quality of life, increased mortality, and increased medical costs. Respiratory therapists must perform complex and time-consuming ventilator weaning assessments...

Extracting Multifaceted Characteristics of Patients With Chronic Disease Comorbidity: Framework Development Using Large Language Models.

JMIR medical informatics
BACKGROUND: Research on chronic multimorbidity has increasingly become a focal point with the aging of the population. Many studies in this area require detailed patient characteristic information. However, the current methods for extracting such inf...

The Advanced Reasoning Capabilities of Large Language Models for Detecting Contraindicated Options in Medical Exams.

JMIR medical informatics
Enhancing clinical reasoning and reducing diagnostic errors are essential in medical practice; OpenAI-o1, with advanced reasoning capabilities, performed better than GPT-4 on 15 Japanese National Medical Licensing Examination questions (accuracy: 100...

Transformer-Based Language Models for Group Randomized Trial Classification in Biomedical Literature: Model Development and Validation.

JMIR medical informatics
BACKGROUND: For the public health community, monitoring recently published articles is crucial for staying informed about the latest research developments. However, identifying publications about studies with specific research designs from the extens...

Comparing Diagnostic Accuracy of Clinical Professionals and Large Language Models: Systematic Review and Meta-Analysis.

JMIR medical informatics
BACKGROUND: With the rapid development of artificial intelligence (AI) technology, especially generative AI, large language models (LLMs) have shown great potential in the medical field. Through massive medical data training, it can understand comple...