AIMC Topic: Health Services Research
Clear Filters Showing 41 to 50 of 50 articles
Improving Mental Health Services: A 50-Year Journey from Randomized Experiments to Artificial Intelligence and Precision Mental Health.
Administration and policy in mental health
Sep 1, 2020
This conceptual paper describes the current state of mental health services, identifies critical problems, and suggests how to solve them. I focus on the potential contributions of artificial intelligence and precision mental health to improving ment...
Can we learn individual-level treatment policies from clinical data?
Biostatistics (Oxford, England)
Apr 1, 2020
Regulatory oversight, causal inference, and safe and effective health care machine learning.
Biostatistics (Oxford, England)
Apr 1, 2020
In recent years, the applications of Machine Learning (ML) in the health care delivery setting have grown to become both abundant and compelling. Regulators have taken notice of these developments and the U.S. Food and Drug Administration (FDA) has b...
Teaching yourself about structural racism will improve your machine learning.
Biostatistics (Oxford, England)
Apr 1, 2020
In this commentary, we put forth the following argument: Anyone conducting machine learning in a health-related domain should educate themselves about structural racism. We argue that structural racism is a critical body of knowledge needed for gener...
Assessing the field of health policy and systems research using symposium abstract submissions and machine learning techniques.
Health policy and planning
Dec 1, 2019
The field of health policy and systems research (HPSR) has grown rapidly in the past decade. Examining recently aggregated data from the Global Symposia on Health Systems Research, a key global fora for HPSR convened by the largest international soci...
Machine Learning for Health Services Researchers.
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
Jul 1, 2019
BACKGROUND: Machine learning is increasingly used to predict healthcare outcomes, including cost, utilization, and quality.
Real-World Evidence, Causal Inference, and Machine Learning.
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
May 1, 2019
The current focus on real world evidence (RWE) is occurring at a time when at least two major trends are converging. First, is the progress made in observational research design and methods over the past decade. Second, the development of numerous la...
Big data and machine learning algorithms for health-care delivery.
The Lancet. Oncology
May 1, 2019
Analysis of big data by machine learning offers considerable advantages for assimilation and evaluation of large amounts of complex health-care data. However, to effectively use machine learning tools in health care, several limitations must be addre...
Health computing for Intelligence of Things.
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2019
[Algorithms, machine intelligence, big data : general considerations].
Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
Aug 1, 2015
We are experiencing astonishing developments in the areas of big data and artificial intelligence. They follow a pattern that we have now been observing for decades: according to Moore's Law,the performance and efficiency in the area of elementary ar...
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