Veranstalter: Fachbereich Informatik
A verbal autopsy is a post-hoc written interview report of the symptoms preceding a person’s death in cases where no official cause of death was determined by a physician. Current leading automated prediction methods primarily use structured data from verbal autopsies to assign a cause-of-death category. We present a neural-net-based classification method based on textual features to automatically predict cause-of-death categories from free-text verbal autopsy narratives alone. Features used, in addition to lexical cues, include events, temporal sequences, and symptom words. We are presently porting the system from English to Hindi. (Joint work with Serena Jeblee, Mireille Gomes, Parthkumar Parmar, Yoona Park,and Prabhat Jha.)
Vita: Graeme Hirst is a computer scientist at the University of Toronto. His research covers a broad range of topics in applied computational linguistics and natural language processing, including lexical semantics, the resolution of ambiguity in text, the analysis of authors’ styles in literature and other text, and the automatic analysis of arguments and discourse (especially in political and parliamentary texts). Hirst’s recent research includes detecting markers of Alzheimer’s disease in language; determining ideology in political texts; and the identification of the native language of a second-language writer of English. With colleagues in Canada, the U.K. and the Netherlands, he was a co-PI of a Digging Into Data grant on processing linked parliamentary data.
He is the author of two monographs: Anaphora in Natural Language Understanding and Semantic Interpretation and the Resolution of Ambiguity. He is the editor of the series Synthesis Lectures on Human Language Technologies (Morgan & Claypool Publishers), which has become the leading venue for monograph publication in computational linguistics and natural language processing. He was also one of the six coordinating editors of the 14-volume Encyclopedia of Language and Linguistics (2nd edition), published by Elsevier in 2006. He has supervised 23 PhD and 45 research Master’s graduates, and is the recipient of two awards for excellence in teaching. In 2017, he received the Lifetime Achievement Award from the Canadian Artificial Intelligence Association.
Organisation: Prof. Dr. Iryna Gurevych (firstname.lastname@example.org,
Tel: 06151 / 16-5411)