64 citations · 109 across the 16 of their papers we have counts for
5 papers · 1 filter
Mining Themes in Clinical Notes to Identify Phenotypes and to Predict Length of Stay in Patients admitted with Heart Failure
Ankita Agarwal, Tanvi Banerjee, William L. Romine +3
Heart failure is a syndrome which occurs when the heart is not able to pump blood and oxygen to support other organs in the body. Identifying the underlying themes in the diagnosti…
Predicting Thermoelectric Power Factor of Bismuth Telluride During Laser Powder Bed Fusion Additive Manufacturing
Ankita Agarwal, Tanvi Banerjee, Joy Gockel +3
An additive manufacturing (AM) process, like laser powder bed fusion, allows for the fabrication of objects by spreading and melting powder in layers until a freeform part shape is…
Leveraging Natural Learning Processing to Uncover Themes in Clinical Notes of Patients Admitted for Heart Failure
Ankita Agarwal, Krishnaprasad Thirunarayan, William L. Romine +3
Heart failure occurs when the heart is not able to pump blood and oxygen to support other organs in the body as it should. Treatments include medications and sometimes hospitalizat…
Toward Sensor-based Sleep Monitoring with Electrodermal Activity Measures
William Romine, Tanvi Banerjee, Garrett Goodman
We use self-report and electrodermal activity (EDA) wearable sensor data from 77 nights of sleep on six participants to test the efficacy of EDA data for sleep monitoring. We used…
Early hospital mortality prediction using vital signals
Reza Sadeghi, Tanvi Banerjee, William Romine
Early hospital mortality prediction is critical as intensivists strive to make efficient medical decisions about the severely ill patients staying in intensive care units. As a res…