AIMC Topic: Diabetes Mellitus
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Long-Term Assessment of Rehabilitation Treatment of Sports through Artificial Intelligence Research.
Computational and mathematical methods in medicine
Dec 22, 2021
BACKGROUND: Artificial intelligence (AI) technology has been incorporated into all walks of life, especially the integration of machine learning and health management has achieved very significant progress and results. It is very necessary to analyze...
A stratified analysis of a deep learning algorithm in the diagnosis of diabetic retinopathy in a real-world study.
Journal of diabetes
Dec 9, 2021
BACKGROUND: The aim of our research was to prospectively explore the clinical value of a deep learning algorithm (DLA) to detect referable diabetic retinopathy (DR) in different subgroups stratified by types of diabetes, blood pressure, sex, BMI, age...
A deep learning model for identifying diabetic retinopathy using optical coherence tomography angiography.
Scientific reports
Nov 26, 2021
As the prevalence of diabetes increases, millions of people need to be screened for diabetic retinopathy (DR). Remarkable advances in technology have made it possible to use artificial intelligence to screen DR from retinal images with high accuracy ...
General deep learning model for detecting diabetic retinopathy.
BMC bioinformatics
Nov 8, 2021
BACKGROUND: Doctors can detect symptoms of diabetic retinopathy (DR) early by using retinal ophthalmoscopy, and they can improve diagnostic efficiency with the assistance of deep learning to select treatments and support personnel workflow. Conventio...
An ontology network for Diabetes Mellitus in Mexico.
Journal of biomedical semantics
Oct 9, 2021
BACKGROUND: Medical experts in the domain of Diabetes Mellitus (DM) acquire specific knowledge from diabetic patients through monitoring and interaction. This allows them to know the disease and information about other conditions or comorbidities, tr...
Implementation and evaluation of a multivariate abstraction-based, interval-based dynamic time-warping method as a similarity measure for longitudinal medical records.
Journal of biomedical informatics
Oct 8, 2021
OBJECTIVES: A common prerequisite for tasks such as classification, prediction, clustering and retrieval of longitudinal medical records is a clinically meaningful similarity measure that considers both [multiple] variable (concept) values and their ...
Automated detection of severe diabetic retinopathy using deep learning method.
Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Sep 30, 2021
PURPOSE: The purpose of this study is to develop and validate the intelligent diagnosis of severe DR with lesion recognition based on color fundus photography.
Machine Learning Based Diabetes Classification and Prediction for Healthcare Applications.
Journal of healthcare engineering
Sep 29, 2021
The remarkable advancements in biotechnology and public healthcare infrastructures have led to a momentous production of critical and sensitive healthcare data. By applying intelligent data analysis techniques, many interesting patterns are identifie...
Claims-based algorithms for common chronic conditions were efficiently constructed using machine learning methods.
PloS one
Sep 27, 2021
Identification of medical conditions using claims data is generally conducted with algorithms based on subject-matter knowledge. However, these claims-based algorithms (CBAs) are highly dependent on the knowledge level and not necessarily optimized f...
A Deep Learning Approach to Predict Diabetes' Cardiovascular Complications From Administrative Claims.
IEEE journal of biomedical and health informatics
Sep 3, 2021
People with diabetes require lifelong access to healthcare services to delay the onset of complications. Their disease management processes generate great volumes of data across several domains, from clinical to administrative. Difficulties in access...
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