Using speech and language to identify patients at risk for hospitalizations and emergency department visits in homecare
This study is the first step in exploring an emerging and previously understudied data stream - verbal communication between healthcare providers and patients. In partnership between Columbia Engineering, School of Nursing, Amazon, and the largest home healthcare agency in the US, the study will investigate how to use audio-recorded routine communications between patients and nurses to help identify patients at risk of hospitalization or emergency department visits. The study will combine speech recognition, machine learning and natural language processing to achieve its goals.
This project is eligible for a matching fund stipend from the Data Science Institute. This is not a guarantee of payment, and the total amount is subject to available funding.
Faculty Advisor
- Professor: Zoran kostic
- Center/Lab:
- Location: Shapiro 813
- Kostić uses parallel computing, deep learning, and software/hardware co-design techniques to implement systems and optimize their performance. He was a key contributor to research in mobile wireless systems of second and third generation, and a lead system architect for a system-on-chip deployed in dozens of millions of devices. He uses his integration skills to create complete solutions to problems at scale. He has a vigorous collaboration with industrial partners and academics from engineering and medical fields. He also has extensive intellectual property development and consulting experience.
Project Timeline
- Earliest starting date: 9/13/21
- End date: 12/30/21
- Number of hours per week of research expected during Fall 2021: ~10
- Number of hours per week of research expected during Summer 2021: ~20 or 40
Candidate requirements
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Skill sets: Some combination of: Signal Processing, speech Processing, Data Analysis, Software Development, some background and interest in Cloud Computing, GPUs, Machine Learning, Deep Learning.
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Student eligibility:
freshman,sophomore,junior,senior, master’s -
International students on F1 or J1 visa: eligible
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Academic Credit Possible: Yes