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Mayo Clinic team will use AI to advance mental health research for better patient treatments
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Mayo Clinic researchers will work on a federally funded project to advance research in mental health using big data and machine learning to ultimately improve patient outcomes and personalize treatments.
A grant from the National Institute of Mental Health (NIMH) is a five-year project on which Mayo Clinic will serve as the data coordination center for the Individually Measured Phenotypes to Advance Computational Translation in Mental Health, or IMPACT-MH, program. Mayo researchers will closely collaborate with other grant awardees to help them understand their research data. Mayo is leading the Data Standards core of the study, implementing data standardization for conditions such as depression, anxiety, schizophrenia, sleep disorders and related mental illnesses. The team will leverage both cutting-edge AI techniques and domain expertise, and the result eventually will lead to better treatments for patients.
Mayo also will develop an ontological, or categorical, representation for the Research Domain Criteria established by NIMH as a research framework for mental health disorders. The goal is to improve diagnosis and treatment and hasten cures through new research approaches.
Millions of people suffer from mental illness every year. According to the National Alliance on Mental Illness:
- One in five U.S. adults experiences mental illness each year.
- One in 20 U.S. adults experiences serious mental illness each year.
- One in six U.S. youth aged 6-17 experiences a mental health disorder each year.
There are serious challenges treating mental illness mostly because it is underdiagnosed, under-reported and broadly defined, with a lack of resources available to those who need help, says Cui Tao, Ph.D., chair of Mayo Clinic's Research Department of Artificial Intelligence and Informatics and one of the principal investigators of the project. Dr. Tao is the Nancy Peretsman and Robert Scully Chair of AI and Informatics.
"The field lacks universally accepted, standardized measures for assessing specific conditions, which makes it difficult to aggregate and compare data across studies and settings," says Dr. Tao. In addition, the health system depends on patients' willingness to report their symptoms and follow up with a mental health professional for diagnosis and treatment. These challenges make it difficult to collect and analyze data on various mental health disorders.
The IMPACT-MH program will allow Mayo Clinic scientists to advance artificial intelligence and machine learning so researchers can use the technology to process large data sets on mental health. Researchers will be able to see patterns in illness that could help them identify causes, signs and symptoms while assisting in the selection of the best treatments for patients using refined algorithms.
"Our goal is to establish a FAIR (findable, accessible, interoperable and reusable) data ecosystem for IMPACT-MH, facilitating critical aspects of data management and sharing," says Dr. Tao.
Through collaborative efforts and the utilization of advanced data management and analytics techniques, the researchers hope to make significant contributions to the field and advance the understanding of mental health, benefiting patients. The team will work to integrate data from behavioral assessments, clinical records and biological markers, and to generate more precise and objective clinical disease characteristics, Dr. Tao says.
The Mayo team will collaborate with a Yale University team led by Dr. Hua Xu and a University of Pennsylvania team led by Dr. Yong Chen to enhance the impact and reach of the program's efforts.
