ICBI is collaborating with the US Dept. of Veterans Affairs (VA) and the Georgetown Department of Psychiatry to develop innovative e-Mental Health interventions that leverage our expertise in mHealth and telemedicine. Most recently, we mined acoustic and semantic features from audio interviews to predict suicidal tendencies in military veterans. Using the 208 narrative audios collected from veterans, a classifier was built that differentiates suicidal from non-suicidal veterans based on acoustic features of speech and sentiment analysis of the transcribed narratives. This work, done using tools such as Google speech-to-text and Natural Language Processing (NLP) APIs and Watson Tone Analyzer, was presented in a poster session at the Technology in Psychiatry Summit 2018. Correlating different types of data about the veterans will help identify veterans at higher risk of suicide in a clinical setting. Figure below shows the workflow diagram for this project.
Detecting nuclei in pathology images using deep learning
Our team participated in the 2018 Data Science Bowl, an online challenge to automatically detect nuclei from any pathology images. Out of more than 68,000 algorithms submitted by participants all over the world, our team scored in the top 12%. Collaborators included Faculty in Department of Pathology.
These are two recent examples. Other projects are underway
Sponsor: GHUCCTS Pilot Projects