AI Medical Compendium Topic

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Diabetes Mellitus, Type 2

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An interpretable predictive deep learning platform for pediatric metabolic diseases.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Metabolic disease in children is increasing worldwide and predisposes a wide array of chronic comorbid conditions with severe impacts on quality of life. Tools for early detection are needed to promptly intervene to prevent or slow the de...

A machine learning prediction model for cancer risk in patients with type 2 diabetes based on clinical tests.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: The incidence of type 2 diabetes is rapidly increasing worldwide. Studies have shown that it is also associated with cancer-related morbidities. Early detection of cancer in patients with type 2 diabetes is crucial.

Association between serum Galectin-3 and periodontitis in patients with type 2 diabetes mellitus.

Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology
OBJECTIVES: This study aims to investigate the correlation between serum Galectin-3 levels and the risk of periodontitis in patients with type 2 diabetes mellitus (T2DM).

Deep learning algorithms to detect diabetic kidney disease from retinal photographs in multiethnic populations with diabetes.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To develop a deep learning algorithm (DLA) to detect diabetic kideny disease (DKD) from retinal photographs of patients with diabetes, and evaluate performance in multiethnic populations.

DETERMINATION OF THE PRA POSITIVITY PERCENTAGE IN MALE PATIENTS WITH CHRONIC KIDNEY DISEASE BY USING FLOW CYTOMETRY TECHNIQUE.

Acta clinica Croatica
The antibodies directed against human leukocyte antigen (HLA) molecules, which play a crucial role in allograft histocompatibility, are called anti-HLA antibodies. Anti-HLA antibodies against foreign HLA molecules may be present in patients with chro...

Deep Learning Algorithm Detects Presence of Disorganization of Retinal Inner Layers (DRIL)-An Early Imaging Biomarker in Diabetic Retinopathy.

Translational vision science & technology
PURPOSE: To develop and train a deep learning-based algorithm for detecting disorganization of retinal inner layers (DRIL) on optical coherence tomography (OCT) to screen a cohort of patients with diabetic retinopathy (DR).

Predicting Long-Term Type 2 Diabetes with Artificial Intelligence (AI): A Scoping Review.

Studies in health technology and informatics
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder that affects a significant portion of the global population. Artificial intelligence (AI) has emerged as a promising tool for predicting T2DM risk. To provide an overview of the AI techn...

A knowledge-based decision support system for inferring supportive treatment recommendations for diabetes mellitus.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Diabetes Mellitus (DM) is a significant risk, mostly causing blindness, kidney failure, heart attack, stroke, and lower limb amputation. A Clinical Decision Support System (CDSS) can assist healthcare practitioners in their daily effort a...

TVAR: assessing tissue-specific functional effects of non-coding variants with deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Analysis of whole-genome sequencing (WGS) for genetics is still a challenge due to the lack of accurate functional annotation of non-coding variants, especially the rare ones. As eQTLs have been extensively implicated in the genetics of h...

Clinical significance of hepatic function in Graves disease with type 2 diabetic mellitus: A single-center retrospective cross-sectional study in Taiwan.

Medicine
Graves disease (GD) and type 2 diabetes mellitus (T2DM) both impair liver function; we therefore explored the possibility of a relationship among diabetic control, thyroid function, and liver function. This retrospective, cross-sectional study compar...