Videos

With a growing range of frauds in the healthcare industry ranging up to 3-10% of total spending in the US, it is essential for healthcare ecosystem not only to protect sensitive healthcare records but also to minimize transactions that are anomalous. On the other hand, regulatory practices prompt us to remove bias and discriminatory recommendations, which often result in poor treatment, inaccurate diagnoses, or leading to delays in diagnosis. In this session, Sharmistha will bring forth how Responsible AI concepts can be extended to graph algorithms in the healthcare industry. The talk highlights two important pillars of Responsible AI, privacy and fairness, which helps deal with fraud and bias in the healthcare field. Sharmistha will provide detailed insights on necessary techniques and algorithms on graphs to curb discriminatory practices and fraud. Furthermore, she will demonstrate a simple use case of product recommendations using Neo4j Graph Data Science that can be extended to provide services such as nutritional diet plans, medications, treatment plans, diagnoses/disease predictions, physical activities, and other healthcare services.