AIMC Topic: Diabetes Mellitus

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Metadata information and fundus image fusion neural network for hyperuricemia classification in diabetes.

Computer methods and programs in biomedicine
OBJECTIVE: In diabetes mellitus patients, hyperuricemia may lead to the development of diabetic complications, including macrovascular and microvascular dysfunction. However, the level of blood uric acid in diabetic patients is obtained by sampling p...

Optimization of diabetes prediction methods based on combinatorial balancing algorithm.

Nutrition & diabetes
BACKGROUND: Diabetes, as a significant disease affecting public health, requires early detection for effective management and intervention. However, imbalanced datasets pose a challenge to accurate diabetes prediction. This imbalance often results in...

Recent progress in artificial intelligence and machine learning for novel diabetes mellitus medications development.

Current medical research and opinion
Diabetes mellitus, stemming from either insulin resistance or inadequate insulin secretion, represents a complex ailment that results in prolonged hyperglycemia and severe complications. Patients endure severe ramifications such as kidney disease, vi...

Integrated image-based deep learning and language models for primary diabetes care.

Nature medicine
Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challenges due to a shortage of trained primary care physicians (PCPs), particularly in low-resource settings. Here, to bridge the gaps, we developed an inte...

Machine learning-based prediction of diabetic patients using blood routine data.

Methods (San Diego, Calif.)
Diabetes stands as one of the most prevalent chronic diseases globally. The conventional methods for diagnosing diabetes are frequently overlooked until individuals manifest noticeable symptoms of the condition. This study aimed to address this gap b...

Enhancing Diabetes Management for Older Patients: The Potential Role of ChatGPT.

Geriatrics & gerontology international
Artificial intelligence (AI) technology has the potential to improve diabetes education for older individuals with diabetes. However, as AI becomes integrated into healthcare, it will be important to ensure even greater accuracy and establish a frame...

Unlocking Optimal Glycemic Interpretation: Redefining HbA1c Analysis in Female Patients With Diabetes and Iron-Deficiency Anemia Using Machine Learning Algorithms.

Journal of clinical laboratory analysis
OBJECTIVE: In response to the nuanced glycemic challenges faced by women with iron deficiency anemia (IDA) associated with diabetes, this study uses advanced machine learning algorithms to redefine hemoglobin (Hb)A1c measurement values. We aimed to i...