Natural Language Processing for Healthcare
With recent advancements in Deep Learning followed by successful deployment in natural language processing (NLP) applications such as language understanding, modeling, and translation, the general hope was to achieve yet another success in healthcare domain. Given the vast amount of healthcare data captured in Electronic Medical Records (EMR) in an unstructured fashion, there is an immediate high demand for NLP to facilitate automatic extraction and structuring of clinical data for decision support. Nevertheless, the performance of off-the-shelf NLP on healthcare data has been disappointing. Recently, tremendous efforts have been dedicated by NLP research pioneers to adapt general language NLP for healthcare domain. This talk aims to review current challenges researchers face, and furthermore, reviews some of the most recent success stories.
3 Key Takeaways:
*General overview of state-of-the-art NLP
*How to build a domain-specific NLP pipeline for life science applications
*Review of a few successful applications of NLP in life sciences and how the future will/should look
Amir Tahmasebi is the director of Deep Learning at Enlitic, San Francisco, CA. Before joining Enlitic, Amir was the senior director of Machine Learning and AI at CODAMETRIX, Boston, MA. He also served as a lecturer at MIT, Northeastern University, Boston University, and Columbia University. Prior to CODAMETRIX, Dr. Tahmasebi was a Principal Research Engineer at PHILIPS HealthTech, Cambridge, MA. Dr. Tahmasebi’s research is focused on innovating computer vision and natural language processing solutions for patient clinical context extraction and modeling, clinical outcome analytics and clinical decision support. Dr. Tahmasebi received his PhD degree in Computer Science from the School of Computing, Queen's University, Canada. He is the recipient of the IEEE Best PhD Thesis award and Tanenbaum Post-doctoral Research Fellowship award. He has been serving as area chair for MICCAI and IPCAI conferences. Dr. Tahmasebi has published and presented his work in a number of conferences and journals including NeurIPS, NAACL, MICCAI, IPCAI, IEEE TMI, SPIE, and RSNA. He has also been granted more than 15 patent awards.