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[HTML][HTML] A survey on recent named entity recognition and relationship extraction techniques on clinical texts
Significant growth in Electronic Health Records (EHR) over the last decade has provided an
abundance of clinical text that is mostly unstructured and untapped. This huge amount of …
abundance of clinical text that is mostly unstructured and untapped. This huge amount of …
Multimodal deep learning methods on image and textual data to predict radiotherapy structure names
Simple Summary Structure name standardization is a critical problem in Radiotherapy
planning systems to correctly identify the various Organs-at-Risk, Planning Target Volumes …
planning systems to correctly identify the various Organs-at-Risk, Planning Target Volumes …
[PDF][PDF] Multimodal Deep Learning Methods to Predict Radiotherapy Structure Names using Image and Textual Data from DICOM Files
Physicians often label anatomical structure sets in Digital Imaging and Communications in
Medicine (DICOM) images with nonstandard names. As these names vary widely, the …
Medicine (DICOM) images with nonstandard names. As these names vary widely, the …
Machine Learning Models to automate Radiotherapy Structure Name Standardization
P Bose - 2023 - scholarscompass.vcu.edu
Abstract Structure name standardization is a critical problem in Radiotherapy planning
systems to correctly identify the various Organs-at-Risk, Planning Target Volumes …
systems to correctly identify the various Organs-at-Risk, Planning Target Volumes …
Learning from Multi-Class Imbalanced Big Data with Apache Spark
WC Sleeman IV - 2021 - scholarscompass.vcu.edu
With data becoming a new form of currency, its analysis has become a top priority in both
academia and industry, furthering advancements in high-performance computing and …
academia and industry, furthering advancements in high-performance computing and …