Machine learning to parse breast pathology reports in Chinese
Sign Up to like & getrecommendations! Published in 2018 at "Breast Cancer Research and Treatment"
DOI: 10.1007/s10549-018-4668-3
Abstract: IntroductionLarge structured databases of pathology findings are valuable in deriving new clinical insights. However, they are labor intensive to create and generally require manual annotation. There has been some work in the bioinformatics community to… read more here.
Keywords: breast pathology; machine learning; pathology reports; pathology ... See more keywords
Classifying cancer pathology reports with hierarchical self-attention networks
Sign Up to like & getrecommendations! Published in 2019 at "Artificial intelligence in medicine"
DOI: 10.1016/j.artmed.2019.101726
Abstract: We introduce a deep learning architecture, hierarchical self-attention networks (HiSANs), designed for classifying pathology reports and show how its unique architecture leads to a new state-of-the-art in accuracy, faster training, and clear interpretability. We evaluate… read more here.
Keywords: pathology reports; self attention; pathology; attention networks ... See more keywords
Automated classification of cancer morphology from Italian pathology reports using Natural Language Processing techniques: a rule-based approach.
Sign Up to like & getrecommendations! Published in 2021 at "Journal of biomedical informatics"
DOI: 10.1016/j.jbi.2021.103712
Abstract: Pathology reports represent a primary source of information for cancer registries. Hospitals routinely process high volumes of free-text reports, a valuable source of information regarding cancer diagnosis for improving clinical care and supporting research. Information… read more here.
Keywords: classification; processing; pathology reports; pathology ... See more keywords
Pathology Reports: Discrepancy Patterns of Second Opinions in a Referral Cancer Center
Sign Up to like & getrecommendations! Published in 2023 at "Cancer Investigation"
DOI: 10.1080/07357907.2022.2162072
Abstract: Abstract Objective To evaluate the diagnostic mismatch (discrepancy) of pathology reports in consulted specimens referred for second opinion. Materials and Methods This cross-sectional study was conducted at a major cancer center, Omid Hospital. In this… read more here.
Keywords: cancer; pathology reports; mismatch; pathology ... See more keywords
PD19-08 DISCREPANCY IN PATHOLOGY REPORTS UPON SECOND REVIEW OF RADICAL ORCHIECTOMY SPECIMENS FOR TESTICULAR GERM CELL TUMORS
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Urology"
DOI: 10.1097/ju.0000000000000862.08
Abstract: detection included imaging alone (42%), imaging combined with tumor markers (39%), and tumor markers alone (7.4%). LDH was elevated in 26 (15%) cases at relapse, and like in seminoma, never in isolation as the sole… read more here.
Keywords: pathology reports; pathology; relapse; false positive ... See more keywords
Deep Learning for Automated Extraction of Primary Sites From Cancer Pathology Reports
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2017.2700722
Abstract: Pathology reports are a primary source of information for cancer registries which process high volumes of free-text reports annually. Information extraction and coding is a manual, labor-intensive process. In this study, we investigated deep learning… read more here.
Keywords: cancer pathology; pathology reports; deep learning; pathology ... See more keywords
Web Application for the Automated Extraction of Diagnosis and Site From Pathology Reports for Keratinocyte Cancers
Sign Up to like & getrecommendations! Published in 2020 at "JCO Clinical Cancer Informatics"
DOI: 10.1200/cci.19.00152
Abstract: PURPOSE Keratinocyte cancers are exceedingly common in high-risk populations, but accurate measures of incidence are seldom derived because the burden of manually reviewing pathology reports to extract relevant diagnostic information is excessive. Thus, we sought… read more here.
Keywords: web application; pathology; site; pathology reports ... See more keywords
Exploiting Rules to Enhance Machine Learning in Extracting Information From Multi-Institutional Prostate Pathology Reports.
Sign Up to like & getrecommendations! Published in 2020 at "JCO clinical cancer informatics"
DOI: 10.1200/cci.20.00028
Abstract: PURPOSE Literature on clinical note mining has highlighted the superiority of machine learning (ML) over hand-crafted rules. Nevertheless, most studies assume the availability of large training sets, which is rarely the case. For this reason,… read more here.
Keywords: pathology; prostate pathology; machine; pathology reports ... See more keywords
Leveraging Natural Language Processing to Extract Features of Colorectal Polyps From Pathology Reports for Epidemiologic Study.
Sign Up to like & getrecommendations! Published in 2023 at "JCO clinical cancer informatics"
DOI: 10.1200/cci.22.00131
Abstract: PURPOSE Histopathologic features are critical for studying risk factors of colorectal polyps, but remain deeply embedded within unstructured pathology reports, requiring costly and time-consuming manual abstraction for research. In this study, we developed and evaluated… read more here.
Keywords: features colorectal; pathology reports; pathology; colorectal polyps ... See more keywords
Evolution of anatomic pathology workload from 2011 to 2019 assessed in a regional hospital laboratory via 574,093 pathology reports
Sign Up to like & getrecommendations! Published in 2021 at "PLoS ONE"
DOI: 10.1371/journal.pone.0253876
Abstract: Objective Quantify changes in workload in relation to the anatomic pathologist workforce. Methods In house pathology reports for cytology and surgical specimens from a regional hospital laboratory over a nine- year period (2011–2019) were analyzed,… read more here.
Keywords: workload; pathology reports; hospital laboratory; pathology ... See more keywords
Developing Customizable Cancer Information Extraction Modules for Pathology Reports Using CLAMP
Sign Up to like & getrecommendations! Published in 2019 at "Studies in health technology and informatics"
DOI: 10.3233/shti190383
Abstract: Natural language processing (NLP) technologies have been successfully applied to cancer research by enabling automated phenotypic information extraction from narratives in electronic health records (EHRs) such as pathology reports; however, developing customized NLP solutions requires… read more here.
Keywords: pathology; information extraction; cancer; pathology reports ... See more keywords