# Jayshree Agarwal

> master of Computer Science & Engineering, University of Washington, 2012

**Wikidata**: [Q113667852](https://www.wikidata.org/wiki/Q113667852)  
**Source**: https://4ort.xyz/entity/jayshree-agarwal

## Summary
Jayshree Agarwal is a computer scientist known for her research in healthcare technology, particularly her work on predicting re-hospitalization risks for heart failure patients. She holds a master’s degree in Computer Science & Engineering from the University of Washington (2012) and has contributed to the intersection of computer science and medical research.

## Biography
- Born: [No data available]
- Nationality: [No data available]
- Education: Master’s degree in Computer Science & Engineering, University of Washington (2012)
- Known for: Research on predicting re-hospitalization risks for congestive heart failure patients
- Employer(s): [No data available]
- Field(s): Computer science, healthcare technology

## Contributions
Jayshree Agarwal’s primary contribution is her master’s thesis, *Predicting Risk of Re-hospitalization for Congestive Heart Failure Patients* (2012), which focused on developing predictive models to improve patient care outcomes. This work addresses a critical challenge in healthcare by leveraging computational methods to identify high-risk patients, enabling proactive medical interventions. While specific implementation details or direct impacts (e.g., adoption by hospitals) are not documented in the source material, the thesis represents a foundational effort in applying computer science to clinical decision-making. Her research aligns with broader trends in healthcare technology, emphasizing data-driven solutions to reduce readmission rates and optimize resource allocation.

## FAQs
### Q: What is Jayshree Agarwal known for?
A: She is recognized for her master’s thesis on predicting re-hospitalization risks for heart failure patients, combining computer science with healthcare research.

### Q: Where did Jayshree Agarwal earn her degree?
A: She earned a master’s degree in Computer Science & Engineering from the University of Washington in 2012.

### Q: What field does Jayshree Agarwal work in?
A: Her work focuses on computer science and healthcare technology, specifically applying predictive modeling to medical challenges.

## Why They Matter
Jayshree Agarwal’s research contributes to the growing field of healthcare technology by addressing practical clinical problems through computational innovation. Her thesis on predicting re-hospitalization risks highlights the potential of machine learning and data analysis to improve patient outcomes and reduce healthcare costs. While her work is specific to congestive heart failure, the methodology could inspire similar approaches for other chronic conditions. By bridging computer science and medicine, Agarwal’s efforts reflect the expanding role of technology in modern healthcare systems, where predictive analytics can enhance decision-making and resource planning.

## Notable For
- Master’s thesis: *Predicting Risk of Re-hospitalization for Congestive Heart Failure Patients* (2012)
- Specialization in healthcare-focused computer science research
- Graduate of the University of Washington’s Computer Science & Engineering program

## Body
### Education and Academic Work
Jayshree Agarwal completed her master’s degree in Computer Science & Engineering at the University of Washington in 2012. Her academic work culminated in a thesis titled *Predicting Risk of Re-hospitalization for Congestive Heart Failure Patients*, supervised by Senjuti Basu Roy. This research applied computational methods to a critical healthcare challenge, demonstrating the practical applications of computer science in medical settings.

### Research Focus
Agarwal’s thesis addressed the prediction of re-hospitalization risks, a significant issue in healthcare due to its implications for patient outcomes and hospital resource management. By developing predictive models, her work aimed to enable earlier interventions for high-risk patients, potentially reducing readmission rates and improving quality of care.

### Professional Background
While specific employment details are not provided, Agarwal’s academic contributions position her within the field of computer science, with a focus on healthcare technology. Her research aligns with industry efforts to integrate data analytics and machine learning into medical practice, reflecting a broader trend toward personalized and predictive healthcare solutions.

## References

1. WorldCat