Unlocking the Power of NLP in Healthcare: The Promise and Perils of Large Language Models
Large language models have revolutionized the field of Natural Language Processing (NLP) and are increasingly being applied in various industries, including healthcare. These models have the potential to greatly improve the efficiency and accuracy of medical data analysis, diagnostics, and treatment. However, their use also brings up a number of ethical and privacy concerns that must be addressed.
This presentation will explore both the promise and perils of using large language models in healthcare. We will discuss the various applications of NLP in healthcare, including medical documentation, sentiment analysis, disease diagnosis, and medical data analysis, and the ways in which large language models are enabling these applications. At the same time, we will also address the potential risks associated with using these models, including data privacy and ethical considerations.
Senior NLP Scientist at Vida
Morteza Noshad is a senior ML/NLP scientist at Vida health. He is skilled at designing large scale NLP models for different healthcare applications such as automated clinical documentation, symptom detection and question answering. Morteza was a research scientist at Stanford University focusing on graph neural networks for clinical decision support systems where he received the SAGE Scientist Award for his research. Morteza received his Ph.D. in Computer Science from University of Michigan where he contributed to the theory of information bottleneck in deep learning.