AIMC Topic: Diabetes Mellitus

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Predicting diabetes second-line therapy initiation in the Australian population via time span-guided neural attention network.

PloS one Oct 18, 2019
INTRODUCTION: The first line of treatment for people with Diabetes mellitus is metformin. However, over the course of the disease metformin may fail to achieve appropriate glycemic control, and a second-line therapy may become necessary. In this pape...
Predictive Value of Tests Female Humans Models, Biological Male Neural Networks, Computer Metformin Diabetes Mellitus Machine Learning Australia
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Predictive models for diabetes mellitus using machine learning techniques.

BMC endocrine disorders Oct 15, 2019
BACKGROUND: Diabetes Mellitus is an increasingly prevalent chronic disease characterized by the body's inability to metabolize glucose. The objective of this study was to build an effective predictive model with high sensitivity and selectivity to be...
Aged Aged, 80 and over Young Adult Adult Prognosis Female Risk Factors Diabetes Mellitus Body Mass Index Follow-Up Studies Models, Statistical Humans Male Machine Learning Middle Aged Biomarkers ROC Curve Canada
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Comparing information extraction techniques for low-prevalence concepts: The case of insulin rejection by patients.

Journal of biomedical informatics Oct 13, 2019
OBJECTIVE: To comparatively evaluate a range of Natural Language Processing (NLP) approaches for Information Extraction (IE) of low-prevalence concepts in clinical notes on the example of decline of insulin therapy recommendation by patients.
Support Vector Machine Natural Language Processing Data Mining Treatment Refusal User-Computer Interface Insulin Humans Hypoglycemic Agents Neural Networks, Computer Diabetes Mellitus Electronic Health Records
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Scoring colorectal cancer risk with an artificial neural network based on self-reportable personal health data.

PloS one Aug 22, 2019
Colorectal cancer (CRC) is third in prevalence and mortality among all cancers in the US. Currently, the United States Preventative Services Task Force (USPSTF) recommends anyone ages 50-75 and/or with a family history to be screened for CRC. To impr...
Male Humans Cardiovascular Diseases Middle Aged Neural Networks, Computer Models, Statistical Health Surveys Risk Factors United States Prognosis Self Report Aged Diabetes Mellitus Female Practice Guidelines as Topic Colorectal Neoplasms Health Status Medical History Taking Early Detection of Cancer
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Automated detection of diabetic subject using pre-trained 2D-CNN models with frequency spectrum images extracted from heart rate signals.

Computers in biology and medicine Aug 9, 2019
In this study, a deep-transfer learning approach is proposed for the automated diagnosis of diabetes mellitus (DM), using heart rate (HR) signals obtained from electrocardiogram (ECG) data. Recent progress in deep learning has contributed significant...
Humans Diabetes Mellitus Signal Processing, Computer-Assisted Heart Rate Models, Cardiovascular Databases, Factual Diagnosis, Computer-Assisted Deep Learning Electrocardiography
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Machine Learning Models can Detect Aneurysm Rupture and Identify Clinical Features Associated with Rupture.

World neurosurgery Jul 9, 2019
BACKGROUND: Machine learning (ML) has been increasingly used in medicine and neurosurgery. We sought to determine whether ML models can distinguish ruptured from unruptured aneurysms and identify features associated with rupture.
Aneurysm, Ruptured Intracranial Aneurysm Diabetes Mellitus Support Vector Machine Hyperlipidemias Smoking Comorbidity Case-Control Studies Hypertension Machine Learning Adult Humans Retrospective Studies Sensitivity and Specificity Female Male Aged Middle Aged
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Variable Selection for Nonparametric Learning with Power Series Kernels.

Neural computation Jul 1, 2019
In this letter, we propose a variable selection method for general nonparametric kernel-based estimation. The proposed method consists of two-stage estimation: (1) construct a consistent estimator of the target function, and (2) approximate the estim...
Diabetes Mellitus Statistics, Nonparametric Post-Cardiac Arrest Syndrome Neoplasms Logistic Models Renal Insufficiency, Chronic Humans Machine Learning Computer Simulation Female Adult
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Ontology-based metabolomics data integration with quality control.

Bioanalysis Jun 10, 2019
 The complications that arise when performing meta-analysis of datasets from multiple metabolomics studies are addressed with computational methods that ensure data quality, completeness of metadata and accurate interpretation across studies. This p...
Metabolomics Humans Quality Control Data Analysis Biological Ontologies Diabetes Mellitus
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How Knowledge Emerges From Artificial Intelligence Algorithm and Data Visualization for Diabetes Management.

Journal of diabetes science and technology May 21, 2019
BACKGROUND: Self-monitoring blood glucose (SMBG) is facilitated by application available to analyze these data. They are mainly based on descriptive statistical analyses. In this study, we are proposing a method inspired by artificial intelligence al...
Blood Glucose Diabetes Mellitus Blood Glucose Self-Monitoring Data Visualization Humans Machine Learning Algorithms
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Artificial intelligence for diabetic retinopathy screening in Africa.

The Lancet. Digital health May 2, 2019
Humans Diabetic Retinopathy Artificial Intelligence Africa Deep Learning Diabetes Mellitus Mass Screening
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