Oliver Rivero-Arias, DPhil, University of Oxford, United Kingdom
Dr. Oliver Rivero-Arias is an Associate Professor at the Nuffield Department of Population Health (NDPH) at the University of Oxford. He is the Senior Health Economist at the National Perinatal Epidemiology Unit based in the NDPH and holds a DPhil in Public Health from the University of Oxford. His main research interests concern the use of robust and appropriate methods to measure and value costs and benefits for the conduct of economic evaluations of interventions during pregnancy, childbirth, the newborn period and early childhood. His research agenda focuses on developing best practices to measure and value health-related quality of life (HRQoL) in cost-effectiveness analysis and he currently leads a programme of work around valuing health to inform healthcare decision-making in child and adolescent populations.
Jinxiang Hu, PhD, University of Kansas Medical Center, United States
Jinxiang Hu is an Associate professor in the Department of Biostatistics & Data Science at the University of Kansas Medical Center. Having completed a Ph.D. degree in Psychometrics and a postdoctoral fellowship at National Institutes of Health, she is experienced in latent variable analysis/measurement models, and Machine Learning/Deep Learning. Jinxiang also collaborates extensively in researching clinical outcomes assessments, cancer, Alzheimer’s Disease, pain studies, quality of life, and cardiology.
Jonathan Shock, PhD, University of Cape Town, South Africa
Jonathan Shock is an Associate Professor in the Department of Mathematics and Applied Mathematics at the University of Cape Town, South Africa. Having completed his PhD in theoretical physics in the UK and completed research positions at the Chinese Academy of Sciences, The University of Santiago de Compostela and the Max Planck Institute for Physics as a Marie Curie fellow, he started working at UCT in 2013 and has since then moved into machine learning research, both on the applied and theoretical sides. His research focus now covers Neuroscience, Reinforcement Learning and Machine Learning for Cognitive and Material Sciences.
Artificial intelligence (AI) is rapidly reshaping the clinical research landscape, leading to major scientific breakthroughs and already making substantial improvements in patients’ lives. A significant amount of investment is making the development of large language models, expected to simulate human intelligence, a reality. Meanwhile important clinical research questions are currently being answered using vast quantities of high-quality data with the help of machine learning techniques. The health outcomes research community can benefit from these advancements, but the application of AI methods in this field requires careful evaluation. At Health and Quality of Life Outcomes, we aim to contribute to the conversation about the application of AI in measuring and valuing health. AI experts Associate Professors Jinxiang Hu and Jonathan Shock are joining our Editors-in-Chief as guest editors for this collection.
This Topical Collection invites authors to submit manuscripts on a wide range of topics regarding:
- AI in measurement and valuation, including using AI to improve the development of new measures
- novel applications of AI in measuring and valuing health
- ethical challenges and data requirements for successful AI implementation in this field.
This Collection welcomes submission of Research articles, Comments, Reviews, Brief Reports, and Study protocols. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal.
Articles for this Collection should be submitted via our submission system, Snapp. Please, select the appropriate Collection title “AI in Measurement and Valuation of Health: Embracing the Revolution, or a Call for a Cautionary Embrace?” under the “Details” tab during the submission stage.
Articles will undergo the journal’s standard peer-review process and are subject to all the journal’s standard policies. Articles will be added to the Collection as they are published.
The Editors have no competing interests with the submissions which they handle through the peer-review process. The peer-review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.
