Dev Conference by Neo4j
Session Track: Data Science
Session Time:
Session description
Mental health problems have posed a serious threat to the global economy with losses amounting to 1.3 trillion US dollars (USD) in 2010 and $1.6 trillion in 2019. This has resulted in serious productivity losses that can trigger an estimated expense of $6 trillion per year by 2030. This talk brings to the forefront how contextual knowledge from knowledge graphs, in the form of textual corpus, eventualities, and contextual relations, can help to link eventualities to decipher the relation between food, biochemicals, and mental illness. In addition, we deep dive into some working models of graph neural networks using Neo4j to understand and learn its role in predicting disease biomarkers, characterising disease processes, and classifying mental diseases. The talk also brings in causal factors behind mental health disease and how Neo4j helps bring in causal factors to reduce these contributing factors, which can lower depression and anxiety. The talk concludes by emphasising the impact on the advancement of precision medicine through the use of knowledge graphs.
Author, Speaker, Google Developer Expert
Sharmistha Chatterjee is an evangelist and seasoned professional in ML and cloud applications. Sharmistha has graduated from Aalto University, has published research papers, and filed patents. She has led digital transformation of clients on verticals ranging from Retail, BFSI, IOT, and Telecom. She has proven-experience in leading teams to develop scalable AI solutions, enabling revenue upliftment of several million dollars. She is a 2X GDE, an author and a multi-award-winning data scientist. Her community contributions include blogging (hackernoon.com, techairesearch.com), speaking at international conferences, and being a startup mentor at Nasscom's deep tech club. She is a guest speaker in universities (like BITs Pilani), WIDS (Women in Datascience by IIMB) and others. She is the co-author of the book 'Platform and Model Design for Responsible AI', which has been sought by Ivy League Professors and industry CTOs.
