AIMC Topic: Outcome Assessment, Health Care

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Machine Learning Applications for optimized mental health outcomes in Asia: Translating Hype to Hope.

Asian journal of psychiatry Feb 24, 2020
Biomedical Research Bibliometrics Data Mining Outcome Assessment, Health Care Humans Asia Machine Learning Mental Disorders Psychiatry
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Application of artificial intelligence using convolutional neural networks in determining the invasion depth of esophageal squamous cell carcinoma.

Esophagus : official journal of the Japan Esophageal Society Jan 24, 2020
OBJECTIVES: In Japan, endoscopic resection (ER) is often used to treat esophageal squamous cell carcinoma (ESCC) when invasion depths are diagnosed as EP-SM1, whereas ESCC cases deeper than SM2 are treated by surgical operation or chemoradiotherapy. ...
Aged, 80 and over Sensitivity and Specificity Male Middle Aged Deep Learning Retrospective Studies Female Reproducibility of Results Aged Outcome Assessment, Health Care Esophageal Squamous Cell Carcinoma Preoperative Care Endoscopic Mucosal Resection Neoplasm Invasiveness Area Under Curve Esophageal Neoplasms Japan Humans Neural Networks, Computer Artificial Intelligence
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A reliable time-series method for predicting arthritic disease outcomes: New step from regression toward a nonlinear artificial intelligence method.

Computer methods and programs in biomedicine Jan 9, 2020
BACKGROUND AND OBJECTIVE: The interrupted time-series (ITS) concept is performed using linear regression to evaluate the impact of policy changes in public health at a specific time. Objectives of this study were to verify, with an artificial intelli...
Humans Hip Outcome Assessment, Health Care Knee Arthroplasty, Replacement, Knee Artificial Intelligence Interrupted Time Series Analysis Linear Models Research Design Arthroplasty, Replacement, Hip Incidence Arthritis, Rheumatoid
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Comparison of Machine Learning Methods With Traditional Models for Use of Administrative Claims With Electronic Medical Records to Predict Heart Failure Outcomes.

JAMA network open Jan 3, 2020
IMPORTANCE: Accurate risk stratification of patients with heart failure (HF) is critical to deploy targeted interventions aimed at improving patients' quality of life and outcomes.
Logistic Models United States Medicare Heart Failure Outcome Assessment, Health Care Aged, 80 and over Male Comorbidity Cohort Studies Humans Machine Learning Electronic Health Records Female Hospitalization Aged
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Safety and immediate effects of Hybrid Assistive Limb in children with cerebral palsy: A pilot study.

Brain & development Nov 5, 2019
PURPOSE: Early intervention is effective for developing motor ability and preventing contractures and deformities in patients with cerebral palsy (CP). Gait training using the newly developed Hybrid Assistive Limb (HAL) shows promise as an interventi...
Humans Female Exercise Therapy Neurological Rehabilitation Outcome Assessment, Health Care Male Range of Motion, Articular Pilot Projects Cerebral Palsy Child Gait Disorders, Neurologic Robotics
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Machine Learning to Predict Anti-Tumor Necrosis Factor Drug Responses of Rheumatoid Arthritis Patients by Integrating Clinical and Genetic Markers.

Arthritis & rheumatology (Hoboken, N.J.) Nov 4, 2019
OBJECTIVE: Accurate prediction of treatment responses in rheumatoid arthritis (RA) patients can provide valuable information on effective drug selection. Anti-tumor necrosis factor (anti-TNF) drugs are an important second-line treatment after methotr...
Adalimumab Outcome Assessment, Health Care Antirheumatic Agents Normal Distribution Etanercept Certolizumab Pegol Predictive Value of Tests Infliximab Genetic Markers Methotrexate Arthritis, Rheumatoid Polymorphism, Single Nucleotide Treatment Outcome Regression Analysis Humans Machine Learning Tumor Necrosis Factor-alpha Female Reproducibility of Results Male Middle Aged Severity of Illness Index
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The hidden information in patient-reported outcomes and clinician-assessed outcomes: multiple sclerosis as a proof of concept of a machine learning approach.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology Oct 28, 2019
Machine learning (ML) applied to patient-reported (PROs) and clinical-assessed outcomes (CAOs) could favour a more predictive and personalized medicine. Our aim was to confirm the important role of applying ML to PROs and CAOs of people with relapsin...
Humans Machine Learning Prognosis Female Severity of Illness Index Adult Outcome Assessment, Health Care Male Multiple Sclerosis Middle Aged Patient Reported Outcome Measures Disease Progression Proof of Concept Study
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Review of outcome measures in PARO robot intervention studies for dementia care.

Geriatric nursing (New York, N.Y.) Oct 24, 2019
The aim of this study was to describe interventions for PARO, as well as the outcomes evaluated and found following use of PARO, and to identify outcome measures in PARO intervention studies for older adults with dementia. Multiple databases (Web of ...
Social Interaction Quality of Life Dementia Robotics Outcome Assessment, Health Care Humans
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Analysis of substance use and its outcomes by machine learning I. Childhood evaluation of liability to substance use disorder.

Drug and alcohol dependence Oct 22, 2019
BACKGROUND: Substance use disorder (SUD) exacts enormous societal costs in the United States, and it is important to detect high-risk youths for prevention. Machine learning (ML) is the method to find patterns and make prediction from data. We hypoth...
Adolescent Child ROC Curve Young Adult Predictive Value of Tests Humans Longitudinal Studies Adult Substance-Related Disorders Machine Learning Male Outcome Assessment, Health Care Female Severity of Illness Index Psychological Techniques Reproducibility of Results
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Applying density-based outlier identifications using multiple datasets for validation of stroke clinical outcomes.

International journal of medical informatics Oct 3, 2019
INTRODUCTION: Clinicians commonly use the modified Rankin Scale (mRS) and the Barthel Index (BI) to measure clinical outcome after stroke. These are potential targets in machine learning models for stroke outcome prediction. Therefore, the quality of...
Treatment Outcome Cluster Analysis Taiwan Stroke Outcome Assessment, Health Care Validation Studies as Topic Datasets as Topic Prospective Studies Female Aged Male Humans Machine Learning Algorithms Research Design
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