AIMC Journal:
JAMA network open

Showing 191 to 200 of 245 articles

Development and Validation of a Machine Learning Individualized Treatment Rule in First-Episode Schizophrenia.

JAMA network open Feb 5, 2020
IMPORTANCE: Little guidance exists to date on how to select antipsychotic medications for patients with first-episode schizophrenia.
Humans Machine Learning Treatment Outcome Young Adult Precision Medicine Models, Statistical Clinical Decision Rules Adult Prognosis Schizophrenia Male Retrospective Studies Antipsychotic Agents Middle Aged Female
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Prospective and External Evaluation of a Machine Learning Model to Predict In-Hospital Mortality of Adults at Time of Admission.

JAMA network open Feb 5, 2020
IMPORTANCE: The ability to accurately predict in-hospital mortality for patients at the time of admission could improve clinical and operational decision-making and outcomes. Few of the machine learning models that have been developed to predict in-h...
Hospitalization Aged Aged, 80 and over Adult Prognosis Retrospective Studies Electronic Health Records Female Machine Learning Hospital Mortality Male Forecasting ROC Curve Middle Aged Area Under Curve Prospective Studies Risk Assessment Models, Biological Humans Hospitals Hospitals, Teaching
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Assessment of a Machine Learning Model Applied to Harmonized Electronic Health Record Data for the Prediction of Incident Atrial Fibrillation.

JAMA network open Jan 3, 2020
IMPORTANCE: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, and its early detection could lead to significant improvements in outcomes through the appropriate prescription of anticoagulation medication. Although a variety of...
Young Adult Adult Male Machine Learning Atrial Fibrillation Middle Aged Electronic Health Records Female Risk Assessment Aged Logistic Models Humans
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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 Electronic Health Records Female Hospitalization Aged Humans Machine Learning
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Use of Machine Learning for Predicting Escitalopram Treatment Outcome From Electroencephalography Recordings in Adult Patients With Depression.

JAMA network open Jan 3, 2020
IMPORTANCE: Social and economic costs of depression are exacerbated by prolonged periods spent identifying treatments that would be effective for a particular patient. Thus, a tool that reliably predicts an individual patient's response to treatment ...
Sensitivity and Specificity Male Middle Aged Depressive Disorder, Major Prognosis Female Reproducibility of Results Adult Electroencephalography Citalopram Antidepressive Agents, Second-Generation Canada Treatment Outcome Support Vector Machine Predictive Value of Tests Humans Machine Learning Biomarkers
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Development and Validation of a Machine Learning Model to Aid Discharge Processes for Inpatient Surgical Care.

JAMA network open Dec 2, 2019
IMPORTANCE: Inpatient overcrowding is associated with delays in care, including the deferral of surgical care until beds are available to accommodate postoperative patients. Timely patient discharge is critical to address inpatient overcrowding and r...
Aged Aged, 80 and over Young Adult Adult Middle Aged Adolescent Time Factors Sensitivity and Specificity Male Machine Learning Prospective Studies Prognosis Female Models, Theoretical Humans Postoperative Care Neural Networks, Computer Patient Discharge
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Machine Learning and Natural Language Processing for Geolocation-Centric Monitoring and Characterization of Opioid-Related Social Media Chatter.

JAMA network open Nov 1, 2019
IMPORTANCE: Automatic curation of consumer-generated, opioid-related social media big data may enable real-time monitoring of the opioid epidemic in the United States.
Opioid-Related Disorders Spatial Analysis Drug Overdose Electronic Data Processing Humans Machine Learning Pennsylvania Cross-Sectional Studies Social Media Natural Language Processing
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Attention-Based Deep Neural Networks for Detection of Cancerous and Precancerous Esophagus Tissue on Histopathological Slides.

JAMA network open Nov 1, 2019
IMPORTANCE: Deep learning-based methods, such as the sliding window approach for cropped-image classification and heuristic aggregation for whole-slide inference, for analyzing histological patterns in high-resolution microscopy images have shown pro...
Datasets as Topic Barrett Esophagus Deep Learning Adenocarcinoma Biopsy Humans Esophageal Neoplasms Neural Networks, Computer Microscopy Computer Simulation
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Machine Learning Approaches to Predict 6-Month Mortality Among Patients With Cancer.

JAMA network open Oct 2, 2019
IMPORTANCE: Machine learning algorithms could identify patients with cancer who are at risk of short-term mortality. However, it is unclear how different machine learning algorithms compare and whether they could prompt clinicians to have timely conv...
Predictive Value of Tests Male Humans Middle Aged Machine Learning Risk Assessment Female Neoplasms Aged
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Trends and Focus of Machine Learning Applications for Health Research.

JAMA network open Oct 2, 2019
IMPORTANCE: The use of machine learning applications related to health is rapidly increasing and may have the potential to profoundly affect the field of health care.
Humans Biomedical Research Machine Learning Delivery of Health Care Health Services Research Congresses as Topic
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