AIMC Topic: Chronic Disease

Clear Filters Showing 281 to 290 of 340 articles

Clustering Event Trajectories with Machine Learning: An Approach for Electronic Healthcare Records.

Studies in health technology and informatics
Multimorbidity is increasingly prevalent as the population ages and individuals with multiple long-term conditions (MLTCs) live longer. Often each condition is treated by a separate clinician, which can lead to harmful drug-drug and drug-disease inte...

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...

Advancing the Use of Longitudinal Electronic Health Records: Tutorial for Uncovering Real-World Evidence in Chronic Disease Outcomes.

Journal of medical Internet research
Managing chronic diseases requires ongoing monitoring of disease activity and therapeutic responses to optimize treatment plans. With the growing availability of disease-modifying therapies, it is crucial to investigate comparative effectiveness and ...

[The development of model of prognostication and minimization of risk of by-effects under combined application of agents for treatment of chronic cardiac deficiency using AI].

Problemy sotsial'noi gigieny, zdravookhraneniia i istorii meditsiny
The chronic cardiac deficiency continues to be one of the leading health care problems requiring innovative solutions. The article presents mathematical algorithm to evaluate drug interactions and targeted to minimize side effects and to optimize chr...

Deep Learning Model for Diagnosing and Classifying Subtypes of Chronic Pulmonary Aspergillosis in Chest CT.

Mycoses
BACKGROUND: Diagnosing chronic pulmonary aspergillosis (CPA) and its subtypes is essential for treatment and prognosis. In clinical practice, inexperienced doctors may overlook the presence of CPA due to overreliance on radiological results. Applying...

Artificial Intelligence in Medical Care - Patients' Perceptions on Caregiving Relationships and Ethics: A Qualitative Study.

Health expectations : an international journal of public participation in health care and health policy
INTRODUCTION: Artificial intelligence (AI) offers several opportunities to enhance medical care, but practical application is limited. Consideration of patient needs is essential for the successful implementation of AI-based systems. Few studies have...

Machine learning-based risk assessment for cardiovascular diseases in patients with chronic lung diseases.

Medicine
The association between chronic lung diseases (CLDs) and the risk of cardiovascular diseases (CVDs) has been extensively recognized. Nevertheless, conventional approaches for CVD risk evaluation cannot fully capture the risk factors (RFs) related to ...

Bridging the Gap in Neonatal Care: Evaluating AI Chatbots for Chronic Neonatal Lung Disease and Home Oxygen Therapy Management.

Pediatric pulmonology
OBJECTIVE: To evaluate the accuracy and comprehensiveness of eight free, publicly available large language model (LLM) chatbots in addressing common questions related to chronic neonatal lung disease (CNLD) and home oxygen therapy (HOT).

Identifying Risk Factors for Graft Failure due to Chronic Rejection < 15 Years Post-Transplant in Pediatric Kidney Transplants Using Random Forest Machine-Learning Techniques.

Pediatric transplantation
BACKGROUND: Chronic rejection forms the leading cause of late graft loss in pediatric kidney transplant recipients. Despite improvement in short-term graft outcomes, chronic rejection impedes comparable progress in long-term graft outcomes.

A machine learning approach to predicting postoperative recurrence in pediatric chronic rhinosinusitis: identification of key metabolic biomarkers.

American journal of otolaryngology
BACKGROUND: Pediatric chronic rhinosinusitis (CRS) is a common chronic inflammatory disease with a high recurrence rate after surgery. This study aimed to construct and validate a machine learning-based predictive model to predict the risk of postope...