Spark NLP in Action

Oncology - Live Demos & Notebooks

Explore Oncology Notes with Spark NLP Models
This demo shows how oncological terms can be detected using Spark NLP Healthcare NER, Assertion Status, and Relation Extraction models. (...)
Identify Anatomical and Oncology entities related to different treatments, and Oncology Entities Related to Diagnosis from Clinical Texts
This demo shows how to extract more than 40 Oncology-related entities including those related to Cancer diagnosis, Staging information, Tumors, Lymph Nodes, and Metastases. Also shows how to extract entities related to Oncology Therapies, Mentions of Treatments, posology information, Tumor Size, Cancer Therapies, and anatomical entities using pretrained Spark NLP clinical models. (...)
Identify Tests, Biomarkers, and their Results
This demo shows how to extract entities Pathology Tests, Imaging Tests, mentions of Biomarkers, and their results from clinical texts using pretrained Spark NLP clinical models. (...)
Identify Demographic Information from Oncology Texts
This demo shows how to extract Demographic information, Age, Gender, and Smoking status from oncology texts. (...)
Detect Assertion Status from Clinics Entities
This demo shows how to detect the assertion status of entities related to oncology (including diagnoses, therapies, and tests), and if a demographic entity refers to the patient or someone else. (...)
Detect Relation Extraction between different Oncological entity types
This demo shows how to identify relations between Clinical entities, Tumor mentions, Anatomical entities, Tests, Biomarkers, Anatomical Entities, Tumor Size, Tumor Finding, Date, and their corresponding using pretrained Oncology Relation Extraction (RE) models. (...)
Resolve Oncology terminology using the ICD-O taxonomy
This model maps oncology terminology to ICD-O codes using Entity Resolvers. (...)