Structured deep embedding model to generate composite clinical indices from electronic health records for early detection of pancreatic cancer

Park, J., Artin, M. G., Lee, K. E., May, B. L., Park, M., Hur, C., & Tatonetti, N. P. (2023). Structured deep embedding model to generate composite clinical indices from electronic health records for early detection of pancreatic cancer. Patterns, 4(1), 100636. https://doi.org/10.1016/j.patter.2022.100636
Authors:
Jiheum Park
Michael G. Artin
Eunah Lee
Benjamin May
Michael Park
Chin Hur
Nicholas P. Tatonetti
Affiliated Authors:
Jiheum Park
Benjamin May
Chin Hur
Nicholas P. Tatonetti
Columbia Affiliation:
Subjects:
Deep Learning Applications in Healthcare (OpenAlex Topic)
Pancreatic Cancer Research and Treatment (OpenAlex Topic)
Deep Learning in Medical Image Analysis (OpenAlex Topic)
Author Keywords:
composite indices
deep embeddings
dsml2: proof-of-concept: data science output has been formulated, implemented, and tested for one domain/problem
electronic health records
model interpretability
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Publication Type:
Article
Unique ID:
10.1016/j.patter.2022.100636
PMID:
36699740
DOI:
10.1016/j.patter.2022.100636
Journal:
Patterns
Publication Date:
Data Source:
OpenAlex
Source Link:
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Record Created: