AIMC Topic: Diabetes Mellitus, Type 2
Clear Filters Showing 281 to 290 of 424 articles
Improved perfusion pattern score association with type 2 diabetes severity using machine learning pipeline: Pilot study.
Journal of magnetic resonance imaging : JMRI
Aug 5, 2018
BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with alterations in the blood-brain barrier, neuronal damage, and arterial stiffness, thus affecting cerebral metabolism and perfusion. There is a need to implement machine-learning methodolog...
Middle Aged
Severity of Illness Index
Pilot Projects
Diabetes Mellitus, Type 2
Aged, 80 and over
Cross-Sectional Studies
Male
Brain Mapping
Humans
Prospective Studies
Perfusion
Brain
Machine Learning
Cognition Disorders
Female
Imaging, Three-Dimensional
Linear Models
Aged
Insulin Resistance
Longitudinal Studies
Magnetic Resonance Imaging
Factors associated with dementia in elderly.
Ciencia & saude coletiva
May 18, 2018
We analyzed the factors associated with dementia in the elderly attended at a memory outpatient clinic of the University of Southern Santa Catarina (UNISUL). This is a cross-sectional study with data analysis of medical records from January 2013 to A...
Pharmacological therapy selection of type 2 diabetes based on the SWARA and modified MULTIMOORA methods under a fuzzy environment.
Artificial intelligence in medicine
Mar 30, 2018
Medication selection for Type 2 Diabetes (T2D) is a challenging medical decision-making problem involving multiple medications that can be prescribed to control the patient's blood glucose. The wide range of hyperglycemia lowering agents with varying...
Application of an artificial neural network model for diagnosing type 2 diabetes mellitus and determining the relative importance of risk factors.
Epidemiology and health
Mar 10, 2018
OBJECTIVES: To identify the most important demographic risk factors for a diagnosis of type 2 diabetes mellitus (T2DM) using a neural network model.
Personalized prediction of drug efficacy for diabetes treatment via patient-level sequential modeling with neural networks.
Artificial intelligence in medicine
Feb 23, 2018
Patients with type 2 diabetes mellitus are generally under continuous long-term medical treatment based on anti-diabetic drugs to achieve the desired glucose level. Thus, each patient is associated with a sequence of multiple records for prescription...
DMTO: a realistic ontology for standard diabetes mellitus treatment.
Journal of biomedical semantics
Feb 6, 2018
BACKGROUND: Treatment of type 2 diabetes mellitus (T2DM) is a complex problem. A clinical decision support system (CDSS) based on massive and distributed electronic health record data can facilitate the automation of this process and enhance its accu...
Comparing Three Data Mining Algorithms for Identifying the Associated Risk Factors of Type 2 Diabetes.
Iranian biomedical journal
Jan 27, 2018
BACKGROUND: Increasing the prevalence of type 2 diabetes has given rise to a global health burden and a concern among health service providers and health administrators. The current study aimed at developing and comparing some statistical models to i...
Machine learning techniques for medical diagnosis of diabetes using iris images.
Computer methods and programs in biomedicine
Jan 11, 2018
BACKGROUND AND OBJECTIVE: Complementary and alternative medicine techniques have shown their potential for the treatment and diagnosis of chronical diseases like diabetes, arthritis etc. On the same time digital image processing techniques for diseas...
Integration of Distributed Services and Hybrid Models Based on Process Choreography to Predict and Detect Type 2 Diabetes.
Sensors (Basel, Switzerland)
Dec 29, 2017
Life expectancy is increasing and, so, the years that patients have to live with chronic diseases and co-morbidities. Type 2 diabetes is one of the most prevalent chronic diseases, specifically linked to being overweight and ages over sixty. Recent s...
Characteristics Associated With Decreased or Increased Mortality Risk From Glycemic Therapy Among Patients With Type 2 Diabetes and High Cardiovascular Risk: Machine Learning Analysis of the ACCORD Trial.
Diabetes care
Dec 26, 2017
OBJECTIVE: Identifying patients who may experience decreased or increased mortality risk from intensive glycemic therapy for type 2 diabetes remains an important clinical challenge. We sought to identify characteristics of patients at high cardiovasc...
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