Research Paper: Artificial Intelligence for Health and Health Care
This study, authored by JASON, an independent group of elite scientists, is of interest to those interested in opportunities and challenges of AI in health and health care. It addresses issues related to Health Diagnostics, Devices and Apps related for data collection and analysis, advancing algorithm development, large scale data and related issues.
This study, authored by Ahmad Ghany a and Karim Keshavjee explains how processes that “clean” data and “data discipline” can lead to significantly reduced health care costs in managing chronic disease – in particular – Diabetes. This article is of interest to physicians and policy makers considering the benefit of EMR systems.
Poster: Improving the Accuracy of Identifying Patients with Hypertension in Electronic Medical Record Systems
This poster was presented on behalf of InfoClin Analytics at the Institute of Health Policy, Management and Evaluation. This research shows the benefit to patients with hypertension and physicans of applying advanced analytics to EMR data. The analytics applied to EMR data accurately identified 22% more hypertensive patients than physicians could identify.
Poster: Identifying Patients with Cancer in Electronic Medical Records
This poster was presented on behalf of InfoClin Analytics at the 2018 Princess Margaret Cancer Conference. The research shows the benefit of using advanced algorithms to accurately identify patients with prostate or breast cancer. A Simple Search misses as many as 37% and 42% of cases, respectively for breast and prostate cancer and it misidentifies about 13% of patients.
Poster: Advanced Patient Engagement
This poster was presented on behalf of InfoClin Analytics at Association of Family Health Teams of Ontario (AFTHO). The research shows that by using InfoClin Triage, physicians are able to identify and see more high risk patients.