AIMC Topic: Health Services Research

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Intersections of machine learning and epidemiological methods for health services research.

International journal of epidemiology
The field of health services research is broad and seeks to answer questions about the health care system. It is inherently interdisciplinary, and epidemiologists have made crucial contributions. Parametric regression techniques remain standard pract...

[Integrating Artificial Intelligence Into Healthcare Research].

Hu li za zhi The journal of nursing
The rapid development of artificial intelligence (AI) technologies in recent decades has led to innovation and new development opportunities in many industries. The application of AI technologies in the medical and healthcare sector offers significan...

Can Artificial Intelligence Improve Psychotherapy Research and Practice?

Administration and policy in mental health
Leonard Bickman's article on the future of artificial intelligence (AI) in psychotherapy research paints an encouraging picture of the progress to be made in this field. We support his perspective, but we also offer some cautionary notes about the bo...

Improving Mental Health Services: A 50-Year Journey from Randomized Experiments to Artificial Intelligence and Precision Mental Health.

Administration and policy in mental health
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...

Regulatory oversight, causal inference, and safe and effective health care machine learning.

Biostatistics (Oxford, England)
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)
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
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
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
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...