“Even I can do AI!” Some examples of machine learning in aiding medical education and clinical practice.
Location
E4118
Document Type
Poster
Start Date
30-11-2023 1:05 PM
End Date
30-11-2023 1:45 PM
Description
Abstract
Artificial intelligence (AI) is rapidly becoming an integral part of our modern lives. From a clinical and biomedical perspective, AI promises much for accelerating our diagnostic and prediction abilities as well as better serving the healthcare needs of our communities. However, the speed at which these modalities continue to develop and the ongoing challenge of bridging the divide between the highly technical language of neural networks and its application by non-expert users, has proved a formidable obstacle. In the following study, we present examples of exploratory uses of AI technology by DMU faculty, staff and students and highlight resources as well the application of these technologies to members of the healthcare and medical education community.
Recommended Citation
Brooke, Matthew; Frankova, Daniela; Aoki, Teresa; Ronnebaum, Julie; Wachtfogel, Marc; Wimsatt, Leslie; Gubatina, Ariel; Matz, Donald; and Spocter, Muhammad A., "“Even I can do AI!” Some examples of machine learning in aiding medical education and clinical practice." (2023). DMU Research Symposium. 38.
https://digitalcommons.dmu.edu/researchsymposium/2023rs/2023abstracts/38
“Even I can do AI!” Some examples of machine learning in aiding medical education and clinical practice.
E4118
Abstract
Artificial intelligence (AI) is rapidly becoming an integral part of our modern lives. From a clinical and biomedical perspective, AI promises much for accelerating our diagnostic and prediction abilities as well as better serving the healthcare needs of our communities. However, the speed at which these modalities continue to develop and the ongoing challenge of bridging the divide between the highly technical language of neural networks and its application by non-expert users, has proved a formidable obstacle. In the following study, we present examples of exploratory uses of AI technology by DMU faculty, staff and students and highlight resources as well the application of these technologies to members of the healthcare and medical education community.
