AIMC Topic: Disease Management

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The Use of Machine Learning for Analyzing Real-World Data in Disease Prediction and Management: Systematic Review.

JMIR medical informatics
BACKGROUND: Machine learning (ML) and big data analytics are rapidly transforming health care, particularly disease prediction, management, and personalized care. With the increasing availability of real-world data (RWD) from diverse sources, such as...

Continuous glucose monitoring combined with artificial intelligence: redefining the pathway for prediabetes management.

Frontiers in endocrinology
Prediabetes represents an early stage of glucose metabolism disorder with significant public health implications. Although traditional lifestyle interventions have demonstrated some efficacy in preventing the progression to type 2 diabetes, their lim...

Advancements in artificial intelligence for the diagnosis and management of anterior segment diseases.

Current opinion in ophthalmology
PURPOSE OF REVIEW: The integration of artificial intelligence (AI) in the diagnosis and management of anterior segment diseases has rapidly expanded, demonstrating significant potential to revolutionize clinical practice.

Unveiling the Potential of Large Language Models in Transforming Chronic Disease Management: Mixed Methods Systematic Review.

Journal of medical Internet research
BACKGROUND: Chronic diseases are a major global health burden, accounting for nearly three-quarters of the deaths worldwide. Large language models (LLMs) are advanced artificial intelligence systems with transformative potential to optimize chronic d...

Artificial intelligence in the diagnosis and management of refractive errors.

European journal of ophthalmology
Refractive error is among the leading causes of visual impairment globally. The diagnosis and management of refractive error has traditionally relied on comprehensive eye examinations by eye care professionals, but access to these specialized service...

Change of Heart: Can Artificial Intelligence Transform Infective Endocarditis Management?

Pathogens (Basel, Switzerland)
Artificial intelligence (AI) has emerged as a promising adjunct in the diagnosis and management of infective endocarditis (IE), a disease characterized by diagnostic complexity and significant morbidity. Machine learning (ML) models such as SABIER an...

Artificial intelligence in chronic kidney disease management: a scoping review.

Theranostics
Chronic kidney disease (CKD) is a major public health problem worldwide associated with cardiovascular disease, renal failure, and mortality. To effectively address this growing burden, innovative solutions to management are urgently required. We co...

Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management.

Hypertension (Dallas, Tex. : 1979)
Hypertension presents the largest modifiable public health challenge due to its high prevalence, its intimate relationship to cardiovascular diseases, and its complex pathogenesis and pathophysiology. Low awareness of blood pressure elevation and sub...

Utilization of Machine Learning in the Prediction, Diagnosis, Prognosis, and Management of Chronic Myeloid Leukemia.

International journal of molecular sciences
Chronic myeloid leukemia is a clonal hematologic disease characterized by the presence of the Philadelphia chromosome and the BCR::ABL1 fusion protein. Integrating different molecular, genetic, clinical, and laboratory data would improve the diagnost...

Advanced applications in chronic disease monitoring using IoT mobile sensing device data, machine learning algorithms and frame theory: a systematic review.

Frontiers in public health
The escalating demand for chronic disease management has presented substantial challenges to traditional methods. However, the emergence of Internet of Things (IoT) and artificial intelligence (AI) technologies offers a potential resolution by facili...