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pro vyhledávání: '"MICHALOPOULOS, George"'
Recent studies on automatic note generation have shown that doctors can save significant amounts of time when using automatic clinical note generation (Knoll et al., 2022). Summarization models have been used for this task to generate clinical notes
Externí odkaz:
http://arxiv.org/abs/2305.17364
The International Classification of Diseases (ICD) system is the international standard for classifying diseases and procedures during a healthcare encounter and is widely used for healthcare reporting and management purposes. Assigning correct codes
Externí odkaz:
http://arxiv.org/abs/2204.10408
Autor:
Zhou, Peiyuan, Wong, Andrew K. C., Yang, Yang, Leatherdale, Scott T., Battista, Kate, Butt, Zahid A., Michalopoulos, George, Chen, Helen
COMPASS is a longitudinal, prospective cohort study collecting data annually from students attending high school in jurisdictions across Canada. We aimed to discover significant frequent/rare associations of behavioral factors among Canadian adolesce
Externí odkaz:
http://arxiv.org/abs/2109.01739
Autor:
Martucci, Nicole J., Stoops, John, Bowen, William, Orr, Anne, Cotner, Mary-Claire, Michalopoulos, George K., Bhushan, Bharat, Mars, Wendy M.
Publikováno v:
In The American Journal of Pathology August 2024 194(8):1511-1527
Lexical substitution is the task of generating meaningful substitutes for a word in a given textual context. Contextual word embedding models have achieved state-of-the-art results in the lexical substitution task by relying on contextual information
Externí odkaz:
http://arxiv.org/abs/2107.05132
Autor:
Bano, Shehnaz, Copeland, Matthew A., Stoops, John W., Orr, Anne, Jain, Siddhi, Paranjpe, Shirish, Mooli, Raja Gopal Reddy, Ramakrishnan, Sadeesh K., Locker, Joseph, Mars, Wendy M., Michalopoulos, George K., Bhushan, Bharat
Publikováno v:
In Cellular and Molecular Gastroenterology and Hepatology 2024 18(4)
Contextual word embedding models, such as BioBERT and Bio_ClinicalBERT, have achieved state-of-the-art results in biomedical natural language processing tasks by focusing their pre-training process on domain-specific corpora. However, such models do
Externí odkaz:
http://arxiv.org/abs/2010.10391
In most clinical practice settings, there is no rigorous reviewing of the clinical documentation, resulting in inaccurate information captured in the patient medical records. The gold standard in clinical data capturing is achieved via "expert-review
Externí odkaz:
http://arxiv.org/abs/2010.07816
Autor:
Heidari, Alireza, Michalopoulos, George, Kushagra, Shrinu, Ilyas, Ihab F., Rekatsinas, Theodoros
Record fusion is the task of aggregating multiple records that correspond to the same real-world entity in a database. We can view record fusion as a machine learning problem where the goal is to predict the "correct" value for each attribute for eac
Externí odkaz:
http://arxiv.org/abs/2006.10208
Autor:
Yu, Yan-Ping, Liu, Silvia, Ren, Bao-Guo, Nelson, Joel, Jarrard, David, Brooks, James D., Michalopoulos, George, Tseng, George, Luo, Jian-Hua
Publikováno v:
In The American Journal of Pathology April 2023 193(4):392-403