AI Medical Compendium Journal:
International journal of medical informatics

Showing 1 to 10 of 372 articles

Utilizing artificial intelligence and medical experts to identify predictors for common diagnoses in dyspneic adults: A cross-sectional study of consecutive emergency department patients from Southern Sweden.

International journal of medical informatics
OBJECTIVE: Half of all adult emergency department (ED) visits with a complaint of dyspnea involve acute heart failure (AHF), exacerbation of chronic obstructive pulmonary disease (eCOPD), or pneumonia, which are often misdiagnosed. We aimed to create...

Artificial intelligence in tobacco control: A systematic scoping review of applications, challenges, and ethical implications.

International journal of medical informatics
BACKGROUND: Tobacco use remains a significant global health challenge, contributing substantially to preventable morbidity and mortality. Despite established interventions, outcomes vary due to scalability issues, resource constraints, and limited re...

Show and tell: A critical review on robustness and uncertainty for a more responsible medical AI.

International journal of medical informatics
This critical review explores two interrelated trends: the rapid increase in studies on machine learning (ML) applications within health informatics and the growing concerns about the reproducibility of these applications across different healthcare ...

The accuracy of Machine learning in the prediction and diagnosis of diabetic kidney Disease: A systematic review and Meta-Analysis.

International journal of medical informatics
PURPOSE: Machine learning (ML) has gained attention in diabetes management, particularly for predicting and diagnosing diabetic kidney disease (DKD). However, systematic evidence on its performance remains limited. This study evaluates the predictive...

Evaluation of insulin sensitivity temporal prediction by using quantile regression combined with neural network model.

International journal of medical informatics
BACKGROUND: Stress-induced hyperglycemia, a pathologically high blood glucose level, is a frequent complication in intensive care units. Blood glucose (BG) level control is crucial but challenging due to patient variability. The Stochastic TARgeted (...

Readability, accuracy and appropriateness and quality of AI chatbot responses as a patient information source on root canal retreatment: A comparative assessment.

International journal of medical informatics
AIM: This study aimed to assess the readability, accuracy, appropriateness, and overall quality of responses generated by large language models (LLMs), including ChatGPT-3.5, Microsoft Copilot, and Gemini (Version 2.0 Flash), to frequently asked ques...

Incorporating machine learning and statistical methods to address maternal healthcare disparities in US: A systematic review.

International journal of medical informatics
BACKGROUND: Maternal health disparities are recognized as a significant public health challenge, with pronounced disparities evident across racial, socioeconomic, and geographic dimensions. Although healthcare technologies have advanced, these dispar...

Systematic literature review on the application of explainable artificial intelligence in palliative care studies.

International journal of medical informatics
BACKGROUND: As machine learning models become increasingly prevalent in palliative care, explainability has become a critical factor in their successful deployment in this sensitive field, where decisions can profoundly impact patient health and qual...

Predicting rheumatoid arthritis in the middle-aged and older population using patient-reported outcomes: insights from the SHARE cohort.

International journal of medical informatics
BACKGROUND: In light of global population aging and the increasing prevalence of Rheumatoid Arthritis (RA) with age, strategies are needed to address this public health challenge. Machine learning (ML) may play a vital role in early identification of...

Wet and dry cough classification using cough sound characteristics and machine learning: A systematic review.

International journal of medical informatics
BACKGROUND: Distinguishing between productive (wet) and non-productive (dry) cough types is important for evaluating respiratory health, assisting in differential diagnosis, and monitoring disease progression. However, assessing cough type through th...