Using natural language processing to construct a metastatic breast cancer cohort from linked cancer registry and electronic medical records data
Objectives Most population-based cancer databases lack information on metastatic
recurrence. Electronic medical records (EMR) and cancer registries contain complementary …
recurrence. Electronic medical records (EMR) and cancer registries contain complementary …
Natural language processing approaches to detect the timeline of metastatic recurrence of breast cancer
PURPOSE Electronic medical records (EMRs) and population-based cancer registries
contain information on cancer outcomes and treatment, yet rarely capture information on the …
contain information on cancer outcomes and treatment, yet rarely capture information on the …
Using natural language processing and machine learning to identify breast cancer local recurrence
Background Identifying local recurrences in breast cancer from patient data sets is important
for clinical research and practice. Developing a model using natural language processing …
for clinical research and practice. Developing a model using natural language processing …
Development and use of natural language processing for identification of distant cancer recurrence and sites of distant recurrence using unstructured electronic health …
PURPOSE Large-scale analysis of real-world evidence is often limited to structured data
fields that do not contain reliable information on recurrence status and disease sites. In this …
fields that do not contain reliable information on recurrence status and disease sites. In this …
Identifying breast cancer distant recurrences from electronic health records using machine learning
Accurately identifying distant recurrences in breast cancer from the electronic health records
(EHR) is important for both clinical care and secondary analysis. Although multiple …
(EHR) is important for both clinical care and secondary analysis. Although multiple …
Classification and diagnostic prediction of breast cancer metastasis on clinical data using machine learning algorithms
M Botlagunta, MD Botlagunta, MB Myneni… - Scientific Reports, 2023 - nature.com
Abstract Metastatic Breast Cancer (MBC) is one of the primary causes of cancer-related
deaths in women. Despite several limitations, histopathological information about the …
deaths in women. Despite several limitations, histopathological information about the …
Machine learning algorithms to predict breast cancer recurrence using structured and unstructured sources from electronic health records
L González-Castro, M Chávez, P Duflot, V Bleret… - Cancers, 2023 - mdpi.com
Simple Summary Breast cancer is a heterogeneous disease characterized by different risks
of relapse, which makes it challenging to predict progression and select the most …
of relapse, which makes it challenging to predict progression and select the most …
From free‐text electronic health records to structured cohorts: Onconum, an innovative methodology for real‐world data mining in breast cancer
A Simoulin, N Thiebaut, K Neuberger… - Computer Methods and …, 2023 - Elsevier
Purpose A considerable amount of valuable information is present in electronic health
records (EHRs) however it remains inaccessible because it is embedded into unstructured …
records (EHRs) however it remains inaccessible because it is embedded into unstructured …
Correlating mammographic and pathologic findings in clinical decision support using natural language processing and data mining methods
BACKGROUND A key challenge to mining electronic health records for mammography
research is the preponderance of unstructured narrative text, which strikingly limits usable …
research is the preponderance of unstructured narrative text, which strikingly limits usable …
Using natural language processing to improve efficiency of manual chart abstraction in research: the case of breast cancer recurrence
DS Carrell, S Halgrim, DT Tran… - American journal of …, 2014 - academic.oup.com
The increasing availability of electronic health records (EHRs) creates opportunities for
automated extraction of information from clinical text. We hypothesized that natural language …
automated extraction of information from clinical text. We hypothesized that natural language …