Specific aims Our overall goal is to build multidisciplinary networks around data and implementation science to drive science and translation, and advance improvements in the development, implementation and dissemination of medical evidence, with an examination of social determinants of health and disparities through the lens of Artificial Intelligence (AI). We will focus on generating evidence on substance use, to enhance early detection, prevention efforts and accelerate initiation of and adherence to treatment. The focus will be on exploring uses of AI in big data and in identifying novel sources of data. These include but are not limited to data on the social determinants of health, including social capital, that would be incorporated into the health record and put to use in supporting clinical practice. Patient groups will be represented on the planning committee, on the speakers list and in the target audience. The intended audience includes patients, patient groups, clinical and dissemination and implementation researchers, medical and other health practitioners, social scientists, public health professionals and officials, patients and patient organizations, governmental and other health agencies, data scientists and other stakeholders who are interested in improving our approaches to turning observations into interventions that improve health. The proposed conference serves to plan and set the tone for such discussions, as it will address the topic of AI and health disparities, it will involve around students and junior investigators, and 50% racial minority and women participation as speakers. We will engage disparities populations in the translation and dissemination of research information, it will foster innovative collaborations and if given the opportunity, will create collaborations with the sponsoring NIH institutes as well as public-private partnerships.
Our overall goal in this conference is to build multidisciplinary networks around data and implementation science to drive science and translation, and advance improvements in the development, implementation and dissemination of medical evidence, with an examination of social determinants of health and disparities through the lens of Artificial Intelligence. We will focus on generating evidence on substance use, to enhance early detection, prevention efforts and accelerate initiation of and adherence to treatment.
