Talk1: An algorithm to determine eligibility for genetic screening of breast cancer leading to early identification
Breast cancer is the most common type of cancer in women. BRCA is by far the most common inherited genes mutation linked to breast cancer, which accounts for 10% of breast cancer cases. We made BRCA genetic mutation guidelines much easier for people to use worldwide. We consolidated these complex genetic screening guidelines from multiple sources and leveraged technology to create a simple, intuitive, and intelligent, web-based, user interface, powered by a sophisticated algorithm on the back end, using JavaScript and HTML. We want to help increase the use and adoption of BRCA genetic testing globally on website www.brcatest.org

Talk2: Cardiovascular disease diagnosis
Cardiovascular Disease Diagnosis - Cardiovascular disease causes 25% of deaths in America. Misdiagnosis of cardiovascular disease results in 11,000 American deaths annually, emphasizing the increasing need for improved diagnosis accuracy using A.I. We set out to determine the probability that a given patient has cardiovascular disease using 11 easily accessible features from a data set of 70,000 people. We compared various Machine Learning and Deep Learning models that require only these basic features. We identified and surmounted implementation challenges to develop our final model that allows for versatile applications in rural locations and third-world countries.