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)

Funded by The Federal Ministry for Economic Affairs and Energy; Grant: 01MD19013D, Smart-MD Project, Digital Technologies

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Results for Query ‹ Adenocarcinoma of lung screening ›

Lung cancer – Prevention | Screening

Adenocarcinoma in situ of the lung – Diagnosis

Non-small-cell lung carcinoma – Staging

Lung cancer – Prevention | Other prevention strategies

Non-small-cell lung carcinoma – Staging | Five-year survival rates

Adenocarcinoma in situ of the lung – Epidemiology

Adenocarcinoma of the lung – Histopathology

Fetal adenocarcinoma – Prognosis and survival

Epithelial-myoepithelial carcinoma of the lung – Prognosis and Survival

Small-cell carcinoma – Prognosis

Giant-cell carcinoma of the lung – Treatment

Giant-cell carcinoma of the lung – Prognosis

Mucinous cystadenocarcinoma of the lung – Prognosis and Survival

Adenocarcinoma of the lung – Management

Epithelial-myoepithelial carcinoma of the lung – Staging

Small-cell carcinoma – Epidemiology

Combined small-cell lung carcinoma – Staging

Urachal cancer – Diagnosis

Pulmonary neuroendocrine tumor – Genetics

Pulmonary neuroendocrine tumor – Diagnosis

Mucinous cystadenocarcinoma of the lung – Treatment

Combined small-cell lung carcinoma – Incidence

Signet ring cell carcinoma – Prognosis by organ

Fetal adenocarcinoma – Treatment

Urachal cancer – Histopathology