no code implementations • 7 Feb 2024 • Jerry Yao-Chieh Hu, Thomas Lin, Zhao Song, Han Liu
Specifically, we establish an upper bound criterion for the norm of input query patterns and memory patterns.
1 code implementation • 23 Nov 2023 • Asma Ben Abacha, Alberto Santamaria-Pang, Ho Hin Lee, Jameson Merkow, Qin Cai, Surya Teja Devarakonda, Abdullah Islam, Julia Gong, Matthew P. Lungren, Thomas Lin, Noel C Codella, Ivan Tarapov
The increasing use of medical imaging in healthcare settings presents a significant challenge due to the increasing workload for radiologists, yet it also offers opportunity for enhancing healthcare outcomes if effectively leveraged.
no code implementations • 3 Jun 2023 • Wen-wai Yim, Yujuan Fu, Asma Ben Abacha, Neal Snider, Thomas Lin, Meliha Yetisgen
Here we present the Ambient Clinical Intelligence Benchmark (ACI-BENCH) corpus, the largest dataset to date tackling the problem of AI-assisted note generation from visit dialogue.
1 code implementation • 27 May 2023 • Asma Ben Abacha, Wen-wai Yim, George Michalopoulos, Thomas Lin
To study the correlation between the automatic metrics and manual judgments, we evaluate automatic notes/summaries by comparing the system and reference facts and computing the factual correctness, and the hallucination and omission rates for critical medical facts.
no code implementations • 11 Apr 2023 • Xiaofeng Zhu, Thomas Lin, Vishal Anand, Matthew Calderwood, Eric Clausen-Brown, Gord Lueck, Wen-wai Yim, Cheng Wu
The core challenge in numerous real-world applications is to match an inquiry to the best document from a mutable and finite set of candidates.
no code implementations • WS 2020 • Seppo Enarvi, Marilisa Amoia, Miguel Del-Agua Teba, Brian Delaney, Frank Diehl, Stefan Hahn, Kristina Harris, Liam McGrath, Yue Pan, Joel Pinto, Luca Rubini, Miguel Ruiz, Gag Singh, eep, Fabian Stemmer, Weiyi Sun, Paul Vozila, Thomas Lin, Ranjani Ramamurthy
We discuss automatic creation of medical reports from ASR-generated patient-doctor conversational transcripts using an end-to-end neural summarization approach.