Objective To classify automatically lung tumor-node-metastases (TNM) cancer stages from free-text pathology reports using symbolic rule-based classification
Pathology reports represent a primary source of information for cancer registries. Hospitals routine...
AbstractThe proposed lung cancer stage classification system remains grounded in anatomic characteri...
Abstract Introduction Lung cancer remains the leading cause of cancer mortality worldwide, with one...
Objective To classify automatically lung tumorenodeemetastases (TNM) cancer stages from free-text pa...
Objective: To automatically generate structured reports for cancer, including TNM (Tumour-Node-Metas...
Objectives: This paper describes a system to automatically classify the stage of a lung cancer patie...
Objective: To develop a system for the automatic classification of pathology reports for Cancer Regi...
<p>Pathologic nodal classification and number and level of metastatic lymph nodes.</p
Background: Natural language processing (NLP) is thought to be a promising solution to extract and s...
Background In the era of datafication, it is important that medical data are accurate and structured...
Information about cancer stage in a patient is crucial when clinicians assess treatment progress. De...
AbstractPredicting malignancy of solitary pulmonary nodules from computer tomography scans is a diff...
AbstractWe introduce an extensible and modifiable knowledge representation model to represent cancer...
Cancer staging provides a basis for planning clinical management, but also allows for meaningful ana...
Pathology reports primarily consist of unstructured free text and thus the clinical information cont...
Pathology reports represent a primary source of information for cancer registries. Hospitals routine...
AbstractThe proposed lung cancer stage classification system remains grounded in anatomic characteri...
Abstract Introduction Lung cancer remains the leading cause of cancer mortality worldwide, with one...
Objective To classify automatically lung tumorenodeemetastases (TNM) cancer stages from free-text pa...
Objective: To automatically generate structured reports for cancer, including TNM (Tumour-Node-Metas...
Objectives: This paper describes a system to automatically classify the stage of a lung cancer patie...
Objective: To develop a system for the automatic classification of pathology reports for Cancer Regi...
<p>Pathologic nodal classification and number and level of metastatic lymph nodes.</p
Background: Natural language processing (NLP) is thought to be a promising solution to extract and s...
Background In the era of datafication, it is important that medical data are accurate and structured...
Information about cancer stage in a patient is crucial when clinicians assess treatment progress. De...
AbstractPredicting malignancy of solitary pulmonary nodules from computer tomography scans is a diff...
AbstractWe introduce an extensible and modifiable knowledge representation model to represent cancer...
Cancer staging provides a basis for planning clinical management, but also allows for meaningful ana...
Pathology reports primarily consist of unstructured free text and thus the clinical information cont...
Pathology reports represent a primary source of information for cancer registries. Hospitals routine...
AbstractThe proposed lung cancer stage classification system remains grounded in anatomic characteri...
Abstract Introduction Lung cancer remains the leading cause of cancer mortality worldwide, with one...
DOI
Add to ORKG