Integrating Artificial Intelligence into Mental Health Research:

An Interview with Dr. Abigail Ortiz

By Kateryna Maksyutynska

Artificial intelligence (AI) has established itself as a powerful and transformative tool. This technology allows for the manipulation of large volumes of data to solve various problems, resulting in its application within diverse disciplines ranging from mundane to complex. Specifically, the implementation of AI in healthcare has revolutionized medicine with its ability to optimize algorithms to inform patient care, and in turn, the patient and user experience. Its use is constantly being expanded and perfected, including in the context of mental health research as scientists work to understand the biological underpinnings of mental illnesses.

Dr. Abigail Ortiz, a Clinician Scientist at the Campbell Family Mental Health Research Institute at the Centre for Addiction and Mental Health (CAMH), implements AI in her study of mood disorders. Her research focuses on the use of wearable devices to build personalized clinical prediction models for individuals with bipolar disorder. Utilizing advanced nonlinear techniques, Dr. Ortiz and her multifaceted team of quantum physicists, mathematicians, biomedical engineers, and computational biologists utilize time-series data to forecast episodes of illness. Together, they study the unique architecture of patients’ mood regulation to better understand clinical trajectories and outcomes.

“The one question that, I think, will take my career to solve has to do with mood regulation… We all have good days and bad days. Why do we bounce back from a bad day, and how?”

Dr. Ortiz was inspired by her own use of wearable technology and took the opportunity to translate it to her clinical practice. Depending on the outcomes being studied, collected data ranges from tracking sleep cycles to objective measures of physical activity, all of which are key factors in the progression of the illness. She recognizes that although these devices are not foolproof, they provide more complete data and offer “a window into the physiology of the patient.” Over time, with more data acquisition and model training, these wearables can be universally integrated into clinical practice to serve as a form of personalized and preventative medicine.

Although this technology has great potential, there are important ethical considerations given the intricacy of some of the research questions that AI is being used to solve, and the scale of data that is required to draw conclusions. Dr. Ortiz emphasized that, “Before we get to developing a [prediction] model, we also need to talk about the ethics of using AI or machine learning into these processes, not only because, of course, they can be biased, but also because we need to understand ‘what do we want to do with it’? How can we better serve patients with this information? With all this information, we need to be aware that privacy and confidentiality are critical.”

Therefore, steps must be taken to ensure the safety and confidentiality of data when prediction models are implemented beyond a clinical setting.

Another important consideration is the affordability of wearables to ensure equitable access to these devices. This is pertinent given that socioeconomic status is a predictor of various mental health disorders.1 Therefore, to develop accurate prediction models, it is essential for training data to be captured from diverse populations to allow for broad utilization in the future. Furthermore, as technology rapidly advances and certain populations may have difficulty adapting it into their daily life, the accessibility of such devices must also be considered. Notably, Dr. Ortiz reported that from her experience, elderly research participants were very open to the use of wearables, enjoyed partaking in the research, and were among one of the most adherent groups in terms of collecting the data. This stresses the need for patient engagement in research to seek the perspectives from individuals with lived experience at all stages of the study–from conception to execution. Considering the needs of key stakeholders allows for the construct of studies that answer relevant questions and offers insight on how to best support the collection of quality data. Given that the introduction of AI to healthcare is relatively recent, such partnerships build trusting relationships between patients and the care team through open dialogue.

Dr. Ortiz also took some time to reflect on her scientific journey and offered encouragement for future students hoping to pursue this area of research. In outlining her work, she highlighted that medicine is not limited to techniques just within the field. To foster growth, various skills and practices must be translated from different disciplines to be able to answer complex questions.

“[People felt that] combining mathematics and AI in psychiatry, for years, was just too complicated–not doable. What I would like to share with grad students is that, if you think you have a good project, with a good idea… there is no cutting corners–you have to do the hard work. You have to tolerate the critiques and keep going if you feel that, that’s what you want to do to solve the problem; to help others; to keep moving forward.”

When asked about the future of AI in medicine, Dr. Ortiz had a very positive outlook on its ability to promote patients to take ownership of their health data and take on a more active role in their own care.

“I think it’s not so much that the technology is going to change or it’s that the use of technology is going to change... I think that how we all use [technology] is going to change… and it’s very empowering to see patients own it, for their own health benefit.”

Through this discussion with Dr. Ortiz, it is clear that the use of AI in medicine has the potential to revolutionize the understanding of multifaceted illnesses and provide more personalized treatment to patients. The subsequent integration of these techniques into standard clinical care can offer opportunities for personalized interventions and care, and encourage patients to be engaged in their healthcare. With this field and technology rapidly expanding, there is need for discussion surrounding the security and confidentiality of vulnerable patient data to ensure that it is being used ethically and stored securely. In addition, to facilitate the full integration of AI in medicine, stakeholder engagement is essential to accurately collect data and effectively construct the study design. Overall, AI has the potential to reshape medical care offered to patients and transform the study of dynamic and multifaceted illnesses, such as in the field of mental health.

From everyone at the IMS Magazine, we thank Dr. Abigail Ortiz for sharing her passion for research and the innovative scope of her work in the field of mental health research.

If you would like to read more about Dr. Ortiz’ ongoing study, you can find it on PubMed (ID: 35459150).

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