AIMC Topic: Patient Acceptance of Health Care
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Machine Learning Approaches for Early Prostate Cancer Prediction Based on Healthcare Utilization Patterns.
Studies in health technology and informatics
Jan 14, 2022
The goal of this study was to build a machine learning model for early prostate cancer prediction based on healthcare utilization patterns. We examined the frequency and pattern changes of healthcare utilization in 2916 prostate cancer patients 3 yea...
Emergency department frequent user subgroups: Development of an empirical, theory-grounded definition using population health data and machine learning.
Families, systems & health : the journal of collaborative family healthcare
Mar 1, 2021
Frequent emergency department (ED) use has been operationalized in research, clinical practice, and policy as number of visits to the ED, despite the fact that this definition lacks empirical evidence and theoretical foundation. To date, there are no...
Women's attitudes to the use of AI image readers: a case study from a national breast screening programme.
BMJ health & care informatics
Mar 1, 2021
BACKGROUND: Researchers and developers are evaluating the use of mammogram readers that use artificial intelligence (AI) in clinical settings.
Leveraging Machine Learning to Identify Predictors of Receiving Psychosocial Treatment for Attention Deficit/Hyperactivity Disorder.
Administration and policy in mental health
Sep 1, 2020
This study aimed to identify factors associated with receiving psychosocial treatment for ADHD in a nationally representative sample. Participants were 6630 youth with a parent-reported diagnosis of ADHD from the 2016-2017 National Survey of Children...
Patient Perspectives on the Use of Artificial Intelligence for Skin Cancer Screening: A Qualitative Study.
JAMA dermatology
May 1, 2020
IMPORTANCE: The use of artificial intelligence (AI) is expanding throughout the field of medicine. In dermatology, researchers are evaluating the potential for direct-to-patient and clinician decision-support AI tools to classify skin lesions. Althou...
Observer Variation
Patient Acceptance of Health Care
Grounded Theory
Mass Screening
Early Detection of Cancer
Physician-Patient Relations
Biopsy
Reproducibility of Results
Aged
Adult
Male
Middle Aged
Qualitative Research
Interviews as Topic
Health Services Accessibility
Artificial Intelligence
Female
Melanoma
Skin Neoplasms
Humans
Howard Rodenberg Comments.
American journal of public health
Apr 1, 2020
The right to refuse diagnostics and treatment planning by artificial intelligence.
Medicine, health care, and philosophy
Mar 1, 2020
In an analysis of artificially intelligent systems for medical diagnostics and treatment planning we argue that patients should be able to exercise a right to withdraw from AI diagnostics and treatment planning for reasons related to (1) the physicia...
Does machine learning improve prediction of VA primary care reliance?
The American journal of managed care
Jan 1, 2020
OBJECTIVES: The Veterans Affairs (VA) Health Care System is among the largest integrated health systems in the United States. Many VA enrollees are dual users of Medicare, and little research has examined methods to most accurately predict which vete...
Using applied machine learning to predict healthcare utilization based on socioeconomic determinants of care.
The American journal of managed care
Jan 1, 2020
OBJECTIVES: To determine if it is possible to risk-stratify avoidable utilization without clinical data and with limited patient-level data.
Novel Machine Learning Approach to Identify Preoperative Risk Factors Associated With Super-Utilization of Medicare Expenditure Following Surgery.
JAMA surgery
Nov 1, 2019
IMPORTANCE: Typically defined as the top 5% of health care users, super-utilizers are responsible for an estimated 40% to 55% of all health care costs. Little is known about which factors may be associated with increased risk of long-term postoperati...
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