Dataset: 9.3K articles from Wikipedia (CC BY-SA).
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Made by DATEXIS (Data Science and Text-based Information Systems) at Beuth University of Applied Sciences Berlin

Deep Learning Technology: Sebastian Arnold, Betty van Aken, Paul Grundmann, Felix A. Gers and Alexander Löser. Learning Contextualized Document Representations for Healthcare Answer Retrieval. The Web Conference 2020 (WWW'20)

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Results for Query ‹ BC - Bronchogenic carcinoma risk

Large-cell lung carcinoma – Incidence

Small-cell carcinoma – Epidemiology

Giant-cell carcinoma of the lung – Epidemiology

Giant-cell carcinoma of the lung – Prognosis

Large-cell lung carcinoma – Diagnosis

Epithelial-myoepithelial carcinoma of the lung – Incidence

Small-cell carcinoma – Prognosis

Epithelial-myoepithelial carcinoma of the lung – Prognosis and Survival

Adenosquamous lung carcinoma – Classification

Pulmonary neuroendocrine tumor – Genetics

Large-cell lung carcinoma with rhabdoid phenotype – Epidemiology

Adenosquamous lung carcinoma – Abstract

Squamous-cell carcinoma of the lung – Abstract

Verrucous carcinoma – Cause

Pulmonary neuroendocrine tumor – Abstract

Salivary gland–like carcinoma of the lung – Classification

Salivary gland–like carcinoma of the lung – Abstract

Large-cell lung carcinoma with rhabdoid phenotype – Prognosis

Merkel-cell carcinoma – Epidemiology

Clear-cell adenocarcinoma – Abstract

Squamous-cell carcinoma of the lung – Description

Primary peritoneal carcinoma – Prognosis and treatment

Carcinoma – Epidemiology

Squamous cell carcinoma – Types

Acinic cell carcinoma – Epidemiology