Скачать с ютуб Temporal Relation Extraction from EMR Clinical Text (and Beyond) (Geurgana Savova) в хорошем качестве

Temporal Relation Extraction from EMR Clinical Text (and Beyond) (Geurgana Savova)

Title: Temporal Relation Extraction from EMR Clinical Text (and Beyond) Presenter: Geurgana Savova, Professor and Patricia F. Brennan Chair in the Computational Health Informatics Program (CHIP) at Boston Children’s Hospital and Harvard Medical School Abstract: This talk will focus on the definition of the task of temporal relation extraction from the clinical narrative and computational methods for solving it. It will summarize major developments since 2010 including the recent pre-trained language models and large language models. The talk will also overview the results from the 2024 Chemotherapy Extraction Timeline Shared Task collocated with NAACL 2024. A specific use case in the oncology domain will be discussed. Bio: Prof. Guergana Savova is Professor and Patricia F. Brennan Chair in the Computational Health Informatics Program (CHIP) at Boston Children’s Hospital and Harvard Medical School. She has been in the AI field of Natural Language Processing (NLP) since 1999 when she started working on automatic speech recognition for medical dictations and language models for automatic speech recognition. She later switched to NLP of the clinical narrative during her tenure at Mayo Clinic (2002-2010) and continued after her move to Boston (2010-). Her 2010 paper introducing the Apache Clinical Text and Knowledge Extraction System (cTAKES; https://github.com/apache/ctakes/wiki; https://ctakes.apache.org) has been widely cited and the cTAKES software has been widely used in academia and industry. Prof. Savova has been leading the development of two other open source tools – DeepPhe and DeepPhe-CR (https://deepphe.github.io/) specifically geared towards the oncology domain. Prof. Savova’s lab is funded exclusively by NIH funding to advance NLP of the clinical narrative. She has mentored numerous mentees now successful professionals. Last but very important – Prof. Savova and Prof. Noemie Elhadad are long time collaborators.