AIMC Topic: Machine Learning

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Use of Machine Learning and Hybrid Closed Loop Insulin Delivery at Diabetes Camps.

Diabetes technology & therapeutics Jun 15, 2020
Insulin Diabetes Mellitus, Type 1 Hypoglycemic Agents Insulin Infusion Systems Humans Machine Learning Blood Glucose
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Machine Learning for 3D Kinematic Analysis of Movements in Neurorehabilitation.

Current neurology and neuroscience reports Jun 15, 2020
PURPOSE OF REVIEW: Recent advances in the machine learning field, especially in deep learning, provide the opportunity for automated, detailed, and unbiased analysis of motor behavior. Although there has not yet been wide use of these techniques in t...
Movement Neurological Rehabilitation Neural Networks, Computer Machine Learning Biomechanical Phenomena Humans
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PM concentration estimation using convolutional neural network and gradient boosting machine.

Journal of environmental sciences (China) Jun 14, 2020
Surface monitoring, vertical atmospheric column observation, and simulation using chemical transportation models are three dominant approaches for perception of fine particles with diameters less than 2.5 micrometers (PM) concentration. Here we explo...
Particulate Matter Neural Networks, Computer Weather Machine Learning China
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Improving blood glucose level predictability using machine learning.

Diabetes/metabolism research and reviews Jun 14, 2020
This study was designed to improve blood glucose level predictability and future hypoglycemic and hyperglycemic event alerts through a novel patient-specific supervised-machine-learning (SML) analysis of glucose level based on a continuous-glucose-mo...
Biomarkers Prognosis Female Humans Machine Learning Algorithms Follow-Up Studies Hypoglycemia Israel Blood Glucose Self-Monitoring Adolescent Blood Glucose Young Adult Diabetes Mellitus, Type 1 Adult Male
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Development of a QSAR model to predict hepatic steatosis using freely available machine learning tools.

Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association Jun 14, 2020
There are various types of hepatic steatosis of which non-alcoholic fatty liver disease, which may be caused by exposure to chemicals and environmental pollutants is the most prevalent, representing a potential major health risk. QSAR modelling has t...
Humans Non-alcoholic Fatty Liver Disease Machine Learning Quantitative Structure-Activity Relationship Algorithms Environmental Pollutants
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Automatic wheat ear counting using machine learning based on RGB UAV imagery.

The Plant journal : for cell and molecular biology Jun 14, 2020
In wheat (Triticum aestivum L) and other cereals, the number of ears per unit area is one of the main yield-determining components. An automatic evaluation of this parameter may contribute to the advance of wheat phenotyping and monitoring. There is ...
Aircraft Automation Crop Production Image Processing, Computer-Assisted Remote Sensing Technology Triticum Machine Learning Algorithms
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Preprocedure Application of Machine Learning and Mechanistic Simulations Predicts Likelihood of Paroxysmal Atrial Fibrillation Recurrence Following Pulmonary Vein Isolation.

Circulation. Arrhythmia and electrophysiology Jun 14, 2020
BACKGROUND: Pulmonary vein isolation (PVI) is an effective treatment strategy for patients with atrial fibrillation (AF), but many experience AF recurrence and require repeat ablation procedures. The goal of this study was to develop and evaluate a m...
Patient-Specific Modeling Pulmonary Veins Meglumine Organometallic Compounds Recurrence Models, Cardiovascular Action Potentials Predictive Value of Tests Atrial Fibrillation Heart Rate Catheter Ablation Machine Learning Proof of Concept Study Retrospective Studies Treatment Outcome Female Contrast Media Aged Magnetic Resonance Imaging Male Middle Aged Reproducibility of Results Risk Assessment Risk Factors Diagnosis, Computer-Assisted Humans
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Social media forensics applied to assessment of post-critical incident social reaction: The case of the 2017 Manchester Arena terrorist attack.

Forensic science international Jun 13, 2020
Forensic science is constantly evolving and transforming, reflecting the numerous technological innovations of recent decades. There are, however, continuing issues with the use of digital data, such as the difficulty of handling large-scale collecti...
Forensic Sciences Terrorism Humans Natural Language Processing Machine Learning Data Mining Social Media United Kingdom
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Decision analysis and reinforcement learning in surgical decision-making.

Surgery Jun 13, 2020
BACKGROUND: Surgical patients incur preventable harm from cognitive and judgment errors made under time constraints and uncertainty regarding patients' diagnoses and predicted response to treatment. Decision analysis and techniques of reinforcement l...
Machine Learning Decision Making, Shared Decision Support Techniques Numbers Needed To Treat Surgical Procedures, Operative Clinical Decision-Making Humans Patient Preference Electronic Health Records Decision Trees Attitude to Health Patient-Centered Care
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A machine learning model for detecting invasive ductal carcinoma with Google Cloud AutoML Vision.

Computers in biology and medicine Jun 13, 2020
OBJECTIVES: This study is aimed to assess the feasibility of AutoML technology for the identification of invasive ductal carcinoma (IDC) in whole slide images (WSI).
Humans Neural Networks, Computer Machine Learning Carcinoma, Ductal
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