Zobrazeno 1 - 10
of 250
pro vyhledávání: '"Dligach, Dmitriy"'
Autor:
Chen, Shan, Gallifant, Jack, Guevara, Marco, Gao, Yanjun, Afshar, Majid, Miller, Timothy, Dligach, Dmitriy, Bitterman, Danielle S.
Generative models have been showing potential for producing data in mass. This study explores the enhancement of clinical natural language processing performance by utilizing synthetic data generated from advanced language models. Promising results s
Externí odkaz:
http://arxiv.org/abs/2403.19511
Autor:
Gao, Yanjun, Li, Ruizhe, Caskey, John, Dligach, Dmitriy, Miller, Timothy, Churpek, Matthew M., Afshar, Majid
Electronic Health Records (EHRs) and routine documentation practices play a vital role in patients' daily care, providing a holistic record of health, diagnoses, and treatment. However, complex and verbose EHR narratives overload healthcare providers
Externí odkaz:
http://arxiv.org/abs/2308.14321
The BioNLP Workshop 2023 initiated the launch of a shared task on Problem List Summarization (ProbSum) in January 2023. The aim of this shared task is to attract future research efforts in building NLP models for real-world diagnostic decision suppor
Externí odkaz:
http://arxiv.org/abs/2306.05270
Autor:
Sharma, Brihat, Gao, Yanjun, Miller, Timothy, Churpek, Matthew M., Afshar, Majid, Dligach, Dmitriy
Generative artificial intelligence (AI) is a promising direction for augmenting clinical diagnostic decision support and reducing diagnostic errors, a leading contributor to medical errors. To further the development of clinical AI systems, the Diagn
Externí odkaz:
http://arxiv.org/abs/2306.04551
Autor:
Gao, Yanjun, Dligach, Dmitriy, Miller, Timothy, Churpek, Matthew M, Uzuner, Ozlem, Afshar, Majid
Daily progress notes are common types in the electronic health record (EHR) where healthcare providers document the patient's daily progress and treatment plans. The EHR is designed to document all the care provided to patients, but it also enables n
Externí odkaz:
http://arxiv.org/abs/2303.08038
Autor:
Gao, Yanjun, Dligach, Dmitriy, Miller, Timothy, Caskey, John, Sharma, Brihat, Churpek, Matthew M, Afshar, Majid
The meaningful use of electronic health records (EHR) continues to progress in the digital era with clinical decision support systems augmented by artificial intelligence. A priority in improving provider experience is to overcome information overloa
Externí odkaz:
http://arxiv.org/abs/2209.14901
Autor:
Gao, Yanjun, Dligach, Dmitriy, Miller, Timothy, Xu, Dongfang, Churpek, Matthew M., Afshar, Majid
Automatically summarizing patients' main problems from daily progress notes using natural language processing methods helps to battle against information and cognitive overload in hospital settings and potentially assists providers with computerized
Externí odkaz:
http://arxiv.org/abs/2208.08408
Autor:
Gao, Yanjun, Dligach, Dmitriy, Miller, Timothy, Tesch, Samuel, Laffin, Ryan, Churpek, Matthew M., Afshar, Majid
Applying methods in natural language processing on electronic health records (EHR) data is a growing field. Existing corpus and annotation focus on modeling textual features and relation prediction. However, there is a paucity of annotated corpus bui
Externí odkaz:
http://arxiv.org/abs/2204.03035
Autor:
Gao, Yanjun, Dligach, Dmitriy, Christensen, Leslie, Tesch, Samuel, Laffin, Ryan, Xu, Dongfang, Miller, Timothy, Uzuner, Ozlem, Churpek, Matthew M, Afshar, Majid
Objective: to provide a scoping review of papers on clinical natural language processing (NLP) tasks that use publicly available electronic health record data from a cohort of patients. Materials and Methods: We searched six databases, including biom
Externí odkaz:
http://arxiv.org/abs/2112.05780
Autor:
Lai, Pui Man Rosalind, Akama-Garren, Elliot, Can, Anil, Tirado, Selena-Rae, Castro, Victor M., Dligach, Dmitriy, Finan, Sean, Gainer, Vivian S., Shadick, Nancy A., Savova, Guergana, Murphy, Shawn N., Cai, Tianxi, Weiss, Scott T., Du, Rose
Publikováno v:
In Journal of Clinical Neuroscience August 2024 126:128-134