AIMC Topic: Diabetes Mellitus
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Efficient treatment of outliers and class imbalance for diabetes prediction.
Artificial intelligence in medicine
Feb 10, 2020
Learning from outliers and imbalanced data remains one of the major difficulties for machine learning classifiers. Among the numerous techniques dedicated to tackle this problem, data preprocessing solutions are known to be efficient and easy to impl...
Policy Implications of Artificial Intelligence and Machine Learning in Diabetes Management.
Current diabetes reports
Feb 1, 2020
PURPOSE OF REVIEW: Machine learning (ML) is increasingly being studied for the screening, diagnosis, and management of diabetes and its complications. Although various models of ML have been developed, most have not led to practical solutions for rea...
Prediction of progression from pre-diabetes to diabetes: Development and validation of a machine learning model.
Diabetes/metabolism research and reviews
Jan 14, 2020
AIMS: Identification, a priori, of those at high risk of progression from pre-diabetes to diabetes may enable targeted delivery of interventional programmes while avoiding the burden of prevention and treatment in those at low risk. We studied whethe...
Prognosis
Electronic Health Records
Female
Risk Factors
Humans
Machine Learning
Databases, Factual
Israel
United Kingdom
Prediabetic State
Disease Progression
Cohort Studies
Time Factors
Follow-Up Studies
Patient Selection
Canada
Diabetes Mellitus
Male
Middle Aged
Aged
Risk Assessment
Aged, 80 and over
Adult
A lesson in implementation: A pre-post study of providers' experience with artificial intelligence-based clinical decision support.
International journal of medical informatics
Dec 30, 2019
BACKGROUND: To explore attitudes about artificial intelligence (AI) among staff who utilized AI-based clinical decision support (CDS).
Implementation of machine learning algorithms to create diabetic patient re-admission profiles.
BMC medical informatics and decision making
Dec 12, 2019
BACKGROUND: Machine learning is a branch of Artificial Intelligence that is concerned with the design and development of algorithms, and it enables today's computers to have the property of learning. Machine learning is gradually growing and becoming...
Pulse Wave Velocity and Machine Learning to Predict Cardiovascular Outcomes in Prediabetic and Diabetic Populations.
Journal of medical systems
Dec 9, 2019
Few studies have addressed the predictive value of arterial stiffness determined by pulse wave velocity (PWV) in a high-risk population with no prevalent cardiovascular disease and with obesity, hypertension, hyperglycemia, and preserved kidney funct...
A New Era for Cyborg Science Is Emerging: The Promise of Cyborganic Beings.
Advanced healthcare materials
Nov 28, 2019
Living flesh, hacked beyond known biological borders, and sophisticated machineries, made by humans, are currently being united to address some of the impending challenges in medicine. Imagine biological systems made from smart biomaterials with the ...
Deep supervised learning with mixture of neural networks.
Artificial intelligence in medicine
Nov 18, 2019
Deep Neural Network (DNN), as a deep architectures, has shown excellent performance in classification tasks. However, when the data has different distributions or contains some latent non-observed factors, it is difficult for DNN to train a single mo...
A data-driven approach to predicting diabetes and cardiovascular disease with machine learning.
BMC medical informatics and decision making
Nov 6, 2019
BACKGROUND: Diabetes and cardiovascular disease are two of the main causes of death in the United States. Identifying and predicting these diseases in patients is the first step towards stopping their progression. We evaluate the capabilities of mach...
Validation of a Deep Learning Algorithm for Diabetic Retinopathy.
Telemedicine journal and e-health : the official journal of the American Telemedicine Association
Nov 4, 2019
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