Cargando…

Efficient and Accurate Extracting of Unstructured EHRs on Cancer Therapy Responses for the Development of RECIST Natural Language Processing Tools: Part I, the Corpus

PURPOSE: Electronic health records (EHRs) are created primarily for nonresearch purposes; thus, the amounts of data are enormous, and the data are crude, heterogeneous, incomplete, and largely unstructured, presenting challenges to effective analyses for timely, reliable results. Particularly, resea...

Descripción completa

Detalles Bibliográficos
Autores principales:	Li, Yalun, Luo, Yung-Hung, Wampfler, Jason A., Rubinstein, Samuel M., Tiryaki, Firat, Ashok, Kumar, Warner, Jeremy L., Xu, Hua, Yang, Ping
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	American Society of Clinical Oncology 2020
Materias:	ORIGINAL REPORTS
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7265793/ https://www.ncbi.nlm.nih.gov/pubmed/32364754 http://dx.doi.org/10.1200/CCI.19.00147

Ejemplares similares

Network analysis of unstructured EHR data for clinical research
por: Bauer-Mehren, Anna, et al.
Publicado: ( 201)

Designing an openEHR-Based Pipeline for Extracting and Standardizing Unstructured Clinical Data Using Natural Language Processing
por: Wulff, Antje, et al.
Publicado: (2020)

Predictive structured–unstructured interactions in EHR models: A case study of suicide prediction
por: Bayramli, Ilkin, et al.
Publicado: (2022)

Integrating Structured and Unstructured EHR Data for Predicting Mortality by Machine Learning and Latent Dirichlet Allocation Method
por: Chiu, Chih-Chou, et al.
Publicado: (2023)

RECIST rules
por: Sohaib, Aslam
Publicado: (2012)

Integrating Structured and Unstructured EHR Data Using an FHIR-based Type System: A Case Study with Medication Data
por: Hong, Na, et al.
Publicado: (2018)

RECIST revised: implications for the radiologist. A review article on the modified RECIST guideline
por: van Persijn van Meerten, Els L., et al.
Publicado: (2009)

Accurate approximation to stochastic reaction diffusion on unstructured meshes in STEPS
por: Hepburn, Iain, et al.
Publicado: (2015)

The Modified Response Evaluation Criteria in Solid Tumors (RECIST) Yield a More Accurate Prognoses Than the RECIST 1.1 in Hepatocellular Carcinoma Treated with Transarterial Radioembolization
por: Lee, Jae Seung, et al.
Publicado: (2020)

Toward a Natural Language Interface for EHR Questions
por: Roberts, Kirk, et al.
Publicado: (2015)

iRECIST: how to do it
por: Persigehl, Thorsten, et al.
Publicado: (2020)

Comparison of tumor assessments using RECIST 1.1 and irRECIST, and association with overall survival
por: Manitz, Juliane, et al.
Publicado: (2022)

Response Evaluation and Survival Prediction Following PD‐1 Inhibitor in Patients With Advanced Hepatocellular Carcinoma: Comparison of the RECIST 1.1, iRECIST, and mRECIST Criteria
por: Zhou, Meng, et al.
Publicado: (2021)

Comparison of RECIST 1.0 and RECIST 1.1 in Patients with Metastatic Cancer: A Pooled Analysis
por: Kim, Jung Han, et al.
Publicado: (2015)

Accurate and Reliable Classification of Unstructured Reports on Their Diagnostic Goal Using BERT Models
por: Rietberg, Max Tigo, et al.
Publicado: (2023)

RECIST Applied to Realistic Tumor Models
por: Levine, Zachary H., et al.
Publicado: (2011)

Imaging tumour response: beyond RECIST
por: Koh, Dow-Mu
Publicado: (2014)

Comparison of the RECIST 1.0 and RECIST 1.1 in Non-Small Cell Lung Cancer Treated with Cytotoxic Chemotherapy
por: Choi, Hyun Chang, et al.
Publicado: (2015)

Comparison of the RECIST 1.0 and RECIST 1.1 in patients treated with targeted agents: a pooled analysis and review
por: Kim, Jung Han
Publicado: (2016)

ClustEHR: a tool for generating synthetic EHR data for unsupervised learning experiments.
por: Alexander, Nonie, et al.
Publicado: (2022)

Response assessment in metronomic chemotherapy: RECIST or PERCIST?
por: Agrawal, Archi, et al.
Publicado: (2014)

RECIST criteria: our experience in daily practice
por: De Luca, S, et al.
Publicado: (2015)

A Letter in Support of Real-World RECIST
por: Gajra, Ajeet, et al.
Publicado: (2020)

Comparison of RECIST 1.1 and iRECIST in Patients Treated with Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis
por: Park, Hyo Jung, et al.
Publicado: (2021)

The α-RECIST (RECIST 1.1 Combined With Alpha Fetoprotein): A Novel Tool for Identifying Tumor Response of Conversion-Radiotherapy for Unresectable Hepatocellular Carcinoma Before Hepatectomy
por: Xu, Ying, et al.
Publicado: (2022)

Regarding the Utility of Unstructured Data and Natural Language Processing for Identification of Breast Cancer Recurrence
por: Ritzwoller, Debra P., et al.
Publicado: (2021)

Tumor response evaluation criteria for HCC (hepatocellular carcinoma) treated using TACE (transcatheter arterial chemoembolization): RECIST (response evaluation criteria in solid tumors) version 1.1 and mRECIST (modified RECIST): JIVROSG-0602
por: Sato, Yozo, et al.
Publicado: (2013)

Tapping into unstructured data: integrating unstructured data and textual analytics into business intelligence
por: Inmon, William H, et al.
Publicado: (2008)

Imaging beyond RECIST: CT and MRI in molecular therapies
por: Diederich, Stefan
Publicado: (2012)

Response assessment in daily practice: RECIST and its modifications
por: Sohaib, Aslam
Publicado: (2014)

Imaging biomarkers for evaluating tumor response: RECIST and beyond
por: Ko, Ching-Chung, et al.
Publicado: (2021)

Modeling EHR with the openEHR approach: an exploratory study in China
por: Min, Lingtong, et al.
Publicado: (2018)

Inpatient EHR User Experience and Hospital EHR Safety Performance
por: Classen, David C., et al.
Publicado: (2023)

Physician Opinions about EHR Use by EHR Experience and by Whether the Practice had optimized its EHR Use
por: Jamoom, EW, et al.
Publicado: (2016)

Identification of Prediabetes Discussions in Unstructured Clinical Documentation: Validation of a Natural Language Processing Algorithm
por: Schwartz, Jessica L, et al.
Publicado: (2022)

Obtaining structured clinical data from unstructured data using natural language processing software
por: Lacey, Arron S, et al.
Publicado: (2017)

Natural language processing to convert unstructured COVID-19 chest-CT reports into structured reports
por: Fanni, Salvatore Claudio, et al.
Publicado: (2023)

Harnessing the Power of Large Language Models (LLMs) for Electronic Health Records (EHRs) Optimization
por: Nashwan, Abdulqadir J, et al.
Publicado: (2023)

Electronic health record (EHR) training program identifies a new tool to quantify the EHR time burden and improves providers’ perceived control over their workload in the EHR
por: DiAngi, Yumi T, et al.
Publicado: (2019)

Patterns of response in metastatic NSCLC during PD‐1 or PD‐L1 inhibitor therapy: Comparison of the RECIST 1.1 and iRECIST criteria
por: Liang, Hongge, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_rg8c3eqahr29nm3efiqnltfobq