Communicating Deep Learning Results For Healthcare
Department
Engineering Management and Systems Engineering
Major
Engineering Management with an industrial emphasis
Research Advisor
Canfield, Casey I.
Advisor's Department
Engineering Management and Systems Engineering
Abstract
There is a rising interest in the use of artificial intelligence (AI), such as “deep learning,” in the healthcare industry. AI techniques aim to identify patterns in healthcare data to improve diagnosis and prognosis. This proposal focuses on a large data set that includes health outcomes, treatments, medications, and Medicare/Medicaid costs for patients who have received a liver or kidney transplant. In this project, we will (1) perform a literature review on the use of AI in healthcare and health communications, (2) collect qualitative data on the implications of using data from an AI to make health decisions, and (3) develop an experiment to test approaches for communicating the uncertainty associated with AI findings. Ultimately, this work may lead to the development of a decision tool, such as an app. or web-page, for transplant patients and/ or doctors.
Biography
Luke Andrews was adopted at the age of three and a half from Mogilovo, Belarus and then moved to the United States where he grew up in St. Charles Missouri. Luke is now a junior at the Missouri University of Science and Technology where he is pursuing a B.S in Engineering Management. When Luke is not busy with school work or activities he enjoys spending his time outdoor hiking, cycling, and hunting.
Research Category
Research Proposals
Presentation Type
Poster Presentation
Document Type
Poster
Location
Upper Atrium
Presentation Date
16 Apr 2019, 9:00 am - 3:00 pm
Communicating Deep Learning Results For Healthcare
Upper Atrium
There is a rising interest in the use of artificial intelligence (AI), such as “deep learning,” in the healthcare industry. AI techniques aim to identify patterns in healthcare data to improve diagnosis and prognosis. This proposal focuses on a large data set that includes health outcomes, treatments, medications, and Medicare/Medicaid costs for patients who have received a liver or kidney transplant. In this project, we will (1) perform a literature review on the use of AI in healthcare and health communications, (2) collect qualitative data on the implications of using data from an AI to make health decisions, and (3) develop an experiment to test approaches for communicating the uncertainty associated with AI findings. Ultimately, this work may lead to the development of a decision tool, such as an app. or web-page, for transplant patients and/ or doctors.
