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A Machine Learning-Based Approach for Predicting Patient Punctuality in Ambulatory Care Centers.

International journal of environmental research and public health May 24, 2020
Late-arriving patients have become a prominent concern in several ambulatory care clinics across the globe. Accommodating them could lead to detrimental ramifications such as schedule disruption and increased waiting time for forthcoming patients, wh...
Male Time Factors Logistic Models United States Medicare Humans Appointments and Schedules Neural Networks, Computer Ambulatory Care Machine Learning Female Aged
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Beyond safety drivers: Applying air traffic control principles to support the deployment of driverless vehicles.

PloS one May 21, 2020
By adopting and extending lessons from the air traffic control system, we argue that a nationwide remote monitoring system for driverless vehicles could increase safety dramatically, speed these vehicles' deployment, and provide employment. It is bec...
Automobile Driving Automation Computer Systems Humans Man-Machine Systems United States Artificial Intelligence Aviation Models, Theoretical Software Motor Vehicles Robotics Algorithms Safety
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Natural Language Processing Improves Detection of Nonsevere Hypoglycemia in Medical Records Versus Coding Alone in Patients With Type 2 Diabetes but Does Not Improve Prediction of Severe Hypoglycemia Events: An Analysis Using the Electronic Medical Record in a Large Health System.

Diabetes care May 15, 2020
OBJECTIVE: To determine if natural language processing (NLP) improves detection of nonsevere hypoglycemia (NSH) in patients with type 2 diabetes and no NSH documentation by diagnosis codes and to measure if NLP detection improves the prediction of fu...
United States Predictive Value of Tests Natural Language Processing Hypoglycemia Information Storage and Retrieval International Classification of Diseases Community Health Planning Clinical Decision Rules Adult Male Middle Aged Humans Female Severity of Illness Index Algorithms Aged Diabetes Mellitus, Type 2 Electronic Health Records Aged, 80 and over Young Adult
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A Machine Learning Approach to Management of Heart Failure Populations.

JACC. Heart failure May 6, 2020
BACKGROUND: Heart failure is a prevalent, costly disease for which new value-based payment models demand optimized population management strategies.
Middle Aged Risk Assessment ROC Curve United States Population Surveillance Retrospective Studies Female Aged Aged, 80 and over Male Morbidity Heart Failure Disease Management Humans Machine Learning
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Machine Learning Offers Exciting Potential for Predicting Postprocedural Outcomes: A Framework for Developing Random Forest Models in IR.

Journal of vascular and interventional radiology : JVIR May 4, 2020
PURPOSE: To demonstrate that random forest models trained on a large national sample can accurately predict relevant outcomes and may ultimately contribute to future clinical decision support tools in IR.
Length of Stay Adolescent Time Factors Child, Preschool Child Adult Male Middle Aged Risk Assessment Infant Image-Guided Biopsy Portasystemic Shunt, Transjugular Intrahepatic Iatrogenic Disease Pneumothorax Uterine Artery Embolization Humans Hospital Mortality Infant, Newborn Machine Learning United States Databases, Factual Inpatients Risk Factors Retrospective Studies Data Mining Aged Female Aged, 80 and over Radiography, Interventional Young Adult
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Innovations in research and clinical care using patient-generated health data.

CA: a cancer journal for clinicians Apr 20, 2020
Patient-generated health data (PGHD), or health-related data gathered from patients to help address a health concern, are used increasingly in oncology to make regulatory decisions and evaluate quality of care. PGHD include self-reported health and t...
Humans Artificial Intelligence Delivery of Health Care Biomedical Research Neoplasms United States Morbidity Medical Oncology
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Deep Learning Predicts Total Knee Replacement from Magnetic Resonance Images.

Scientific reports Apr 14, 2020
Knee Osteoarthritis (OA) is a common musculoskeletal disorder in the United States. When diagnosed at early stages, lifestyle interventions such as exercise and weight loss can slow OA progression, but at later stages, only an invasive option is avai...
Female Aged Male Middle Aged Case-Control Studies Humans Prospective Studies Observational Studies as Topic Deep Learning Knee Joint United States Arthroplasty, Replacement, Knee Treatment Outcome Datasets as Topic Magnetic Resonance Imaging Osteoarthritis, Knee
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Machine learning and the future of Medicare fraud detection.

Journal of the American Academy of Dermatology Mar 29, 2020
Clinical Coding Machine Learning Administrative Claims, Healthcare Fraud United States Financial Audit Medicare Data Mining Datasets as Topic
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Real world study for the concordance between IBM Watson for Oncology and clinical practice in advanced non-small cell lung cancer patients at a lung cancer center in China.

Thoracic cancer Mar 19, 2020
BACKGROUND: IBM Watson for Oncology (WFO) provides physicians with evidence-based treatment options. This study was designed to explore the concordance of the suggested therapeutic regimen for advanced non-small cell lung (NSCLC) cancer patients betw...
United States Carcinoma, Non-Small-Cell Lung Follow-Up Studies Patient Selection Practice Guidelines as Topic Evidence-Based Medicine Adenocarcinoma of Lung Male Middle Aged China Decision Support Systems, Clinical Clinical Decision-Making Humans Lung Neoplasms Female Artificial Intelligence Carcinoma, Squamous Cell Prognosis Survival Rate Retrospective Studies
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Multi-modular AI Approach to Streamline Autism Diagnosis in Young Children.

Scientific reports Mar 19, 2020
Autism has become a pressing healthcare challenge. The instruments used to aid diagnosis are time and labor expensive and require trained clinicians to administer, leading to long wait times for at-risk children. We present a multi-modular, machine l...
Humans Machine Learning United States Autism Spectrum Disorder Male Female Diagnosis, Computer-Assisted Sensitivity and Specificity Surveys and Questionnaires Child, Preschool Child
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