AI and analytics are transforming healthcare through the development of more precise algorithms that give unprecedented insights into diagnostics, treatment, and patient outcomes.
- Predictive analytics can be used for estimating the likelihood of a future outcome of a disease based on patterns in the historical data. This can help healthcare providers learn about these outcomes before they occur and take actions in a timely manner especially when a patient’s life depends on a quick reaction time.
- The Internet of Medical Things designates the interconnection of communication-enabled medical-grade devices and their integration to wider-scale health networks in order to improve patients’ health. Because of the critical nature of health-related systems, there are numerous challenges, particularly in terms of reliability, safety, and security. We are focused on improving the Internet of Medical Things using formal methodologies provided by the cyber-physical systems community.
- Withdrawal from public life in response to the COVID-19 crisis has flooded social media with conversations about the global pandemic. A significant proportion of exchanges, particularly on text-focused channels like Facebook and Twitter, are rife with falsehoods and misinformation on healthcare solutions. We are examining features from social media conversations that can help discover, track, and understand the spread of health misinformation. We also intend to identify what percentage of misinformation is generated by intentionally planted bots.
Publications
Carly L. Clayman, Satish M. Srinivasan, Raghvinder S. Sangwan, “Cancer survival analysis using RNA sequencing and Clinical data,” Procedia Computer Science, 168, 2020, pp. 80-87
Carly L. Clayman, Satish M. Srinivasan, Raghvinder S. Sangwan, “K-means clustering and principal components analysis of microarray data of L1000 landmark genes,” Procedia Computer Science, 168, 2020, pp. 97-104.
Tingyan Wang, Yu Tian, and Robin G. Qiu, “Long Short-Term Memory Recurrent Neural Networks for Multiple Diseases Risk Prediction by Leveraging Longitudinal Medical Records,” IEEE Journal of Biomedical and Health Informatics, 2019.
Tingyan Wang, Robin G. Qiu and Ming Yu, “Predictive Modeling of the Progression of Alzheimer’s Disease with Recurrent Neural Networks.,”Sci Rep 8, 9161, 2018.
Youakim Badr and Arthur Gatouillat, “An Application to a Wearable, Multiparametric, Cardiorespiratory Sensor,” Int’l Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018), 2018.
Advisers
Youakim Badr
Partha Mukherjee
Raghu Sangwan
Satish Srinivasan
Robin Qiu
Industry Partners
IQVIA