AI Medical Compendium Topic

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Disease Management

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A Systematic Review of Artificial Intelligence Applications Used for Inherited Retinal Disease Management.

Medicina (Kaunas, Lithuania)
Nowadays, Artificial Intelligence (AI) and its subfields, Machine Learning (ML) and Deep Learning (DL), are used for a variety of medical applications. It can help clinicians track the patient's illness cycle, assist with diagnosis, and offer appropr...

Treatment Effect Heterogeneity.

Evaluation review
This paper considers recent methodological developments in the treatment effects literature, describes their value for applied evaluation work, and suggests next steps. It pays particular attention to documenting the presence of treatment effect hete...

Evaluating the Diagnostic Accuracy and Management Recommendations of ChatGPT in Uveitis.

Ocular immunology and inflammation
INTRODUCTION: Accurate diagnosis and timely management are vital for favorable uveitis outcomes. Artificial Intelligence (AI) holds promise in medical decision-making, particularly in ophthalmology. Yet, the diagnostic precision and management advice...

Advanced deep learning techniques for early disease prediction in cauliflower plants.

Scientific reports
Agriculture plays a pivotal role in the economies of developing countries by providing livelihoods, sustenance, and employment opportunities in rural areas. However, crop diseases pose a significant threat to both farmers' incomes and food security. ...

ChatGPT enters the room: what it means for patient counseling, physician education, academics, and disease management.

Current opinion in ophthalmology
PURPOSE OF REVIEW: This review seeks to provide a summary of the most recent research findings regarding the utilization of ChatGPT, an artificial intelligence (AI)-powered chatbot, in the field of ophthalmology in addition to exploring the limitatio...

The scope of artificial intelligence in retinopathy of prematurity (ROP) management.

Indian journal of ophthalmology
Artificial Intelligence (AI) is a revolutionary technology that has the potential to develop into a widely implemented system that could reduce the dependence on qualified professionals/experts for screening the large at-risk population, especially i...

Machine learning-driven diagnostic signature provides new insights in clinical management of hypertrophic cardiomyopathy.

ESC heart failure
AIMS: In an era of evolving diagnostic possibilities, existing diagnostic systems are not fully sufficient to promptly recognize patients with early-stage hypertrophic cardiomyopathy (HCM) without symptomatic and instrumental features. Considering th...

Artificial intelligence in therapeutic management of hyperlipidemic ocular pathology.

Experimental eye research
Hyperlipidemia has many ocular manifestations, the most prevalent being retinal vascular occlusion. Hyperlipidemic lesions and occlusions to the vessels supplying the retina result in permanent blindness, necessitating prompt detection and treatment....

Role of Artificial Intelligence in Improving Syncope Management.

The Canadian journal of cardiology
Syncope is common in the general population and a common presenting symptom in acute care settings. Substantial costs are attributed to the care of patients with syncope. Current challenges include differentiating syncope from its mimickers, identify...