Welcome to Data Management and Biomedical Data Analytics Lab!
Popular Links
- Cluster Information on Resources (Lab Members Only) - Requires Login
Recent News
Big Data and AI Driven Opioid Epidemic Research
We are working on using large scale electronic health records for opioid epidemic research. Some recent preliminary results are published as follows.
- Identifying Risk of Opioid Use Disorder for Patients Taking Opioid Medications with Deep Learning. Journal of the American Medical Informatics Association (JAMIA). 2021, ocab043.
- Predicting Opioid Overdose Risk of Patients with Opioid Prescriptions Using Electronic Health Records Based on Temporal Deep Learning. Journal of Biomedical Informatics. 2021 Mar 9;116:103725.
- A Large-Scale Retrospective Study of Opioid Poisoning in New York State with Implications for Targeted Interventions. Scientific Reports 11, 5152 (2021).
- Association of Opioid Use Disorder With 2016 Presidential Voting Patterns: A Cross-Sectional Study in New York State at Census Tract Level. JMIR Public Health Surveill 2021;7(4):e23426.
- A Large-Scale Observational Study on the Temporal Trends and Risk Factors of Opioid Overdose: Real-World Evidence for Better Opioids. Drugs - Real World Outcomes. 2021.
We also explore social media to understand the opioid epidemic. Read our recent work on machine learning based detection of suicidality among opioid users on Reddit.
May 14, 2021: Congratulations to Sina for the Young Academics Inventor's Award!
Sina Rashidian was awarded the Young Academics Inventor's Award from Stony Brook University Chapter of the National Academy of Inventors, for his inventions of software for gaze tracking and geocoding healthcare data
2021 NAI Member Induction Ceremony
January 21, 2021: Congratulations to Dr. Yu Wang, Sina Rashidian and Furqan Baig for succcesful defense of their PhDs!
January 1, 2021: The Computer Science and Informatics Summer Research Experience Program (CSIRE) will resume this year in an online form.
August 21, 2020: ACTION-EHR: Patient-Centric Blockchain-Based Electronic Health Record Data Management for Cancer Care.
How can blockchain empower healthcare? Read our work on building blockchain enabled EHR sharing platform for improving cancer care.
April 15, 2020: Our Ph.D. student, Sina Rashidian, was awarded the Graduate Student of the Year at Stony Brook University.
Sina Rashidian was awarded the Graduate Student of the Year award, the highest honor of graduate student employees of the University, for his creativity, leadership and mentorship.
2020 Student Employee & Supervisor of the Year Awards Honor Students
January 9, 2020: We are very grateful for ALS Association to fund us on building EyeCanDo, an eye gaze-based technology using Apple TrueDepth camera to enable communication for ALS patients.
Lack of mobility and communication due to disability seriously limits the personal freedom of ALS patients and can lead to a low quality of life. The progressive loss of independence and connection to the world affects them and their caregivers physically, emotionally, socially, and spiritually. EyeCanDo is an eye gaze-based technology built on top of Apple smart devices (iPad and iPhone) to enable communications for ALS patients.
The project is in collaboration with Dr. Xiaojun Bi.
App Leverages Eye Movement to Assist ALS Patients
August 2, 2019: We have a very successful summer research experience program for K12 Students (CSIRE, again) at Stony Brook University.
In three years, Stony Brook CSIRE grows into a top-notch nationwide research experience program on computer science and informatics for K12 students.
Slide Show
A Summer in CS for HS Students
August 1, 2019: We are awarded $1.14M from National Cancer Institute to develop methods and software for 3D computional digital pathology.
The project "Computational pathology software for integrative cancer research with three-dimensional digital slides" will develop AI, computer vision and big spatial data technologies to advance cancer research and potentially assist pathologists to improve the efficiency and efficacy for clinical diagnosis. In particular, the work will revolutionize digital pathology from 2D to 3D, which provides a 3D “GIS” like map of human tissues. The project is in collaboration with Georgia State University.
News: Creating 3D Digital Pathology to Advance Cancer Research, Diagnostic Practices
