Dec 5, 2018 � This paper investigates a semi-supervised transfer learning framework for radiology report classification across three hospitals.
This paper investigates a semi-supervised transfer learning framework for radiology report classification across three hospitals. The main goal is to leverage�...
This paper investigates a semi-supervised transfer learning framework for radiology report classification across three hospitals to leverage both vastly�...
This paper investigates a semi-supervised transfer learning framework for radiology report classification across three hospitals.
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Does classification use labeled data?
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Application of machine learning techniques for automatic and reliable classification of clinical documents have shown promising results.
Clinical Document Classification Using Labeled and Unlabeled Data Across Hospitals ... Reviewing radiology reports in emergency departments is an essential but�...
Jun 14, 2023 � It often involves assigning labels or tags to different data elements, such as symptoms, diagnoses, procedures, medications, and patient�...
Objective: Application of machine learning techniques for automatic and reliable classification of clinical documents have shown promising results.
In this study, we propose a hierarchical label-wise attention Transformer model (HiLAT) for the explainable prediction of ICD codes from clinical documents.
This paper investigates a semi-supervised transfer learning framework for radiology report classification across three hospitals to leverage both vastly�...
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