Dataset: 9.3K articles from Wikipedia (CC BY-SA).
More datasets: Wikipedia | CORD-19

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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 ‹ Sarcomatoid carcinoma screening

Epithelial-myoepithelial carcinoma of the lung – Prognosis and Survival

Epithelial-myoepithelial carcinoma of the lung – Staging

Giant-cell carcinoma of the lung – Prognosis

Giant-cell carcinoma of the lung – Treatment

Merkel-cell carcinoma – Diagnosis

Non-small-cell lung carcinoma – Staging

Carcinoma – Diagnosis | Staging

Combined small-cell lung carcinoma – Staging

Carcinoma – Epidemiology

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

Merkel-cell carcinoma – Epidemiology

Large-cell lung carcinoma with rhabdoid phenotype – Epidemiology

Large-cell lung carcinoma with rhabdoid phenotype – Prognosis

Small-cell carcinoma – Prognosis

Combined small-cell lung carcinoma – Incidence

Renal cell carcinoma – Prevention

Small-cell carcinoma – Epidemiology

Renal medullary carcinoma – Diagnosis

Large-cell lung carcinoma – Incidence

Renal cell carcinoma – Diagnosis | Radiology | Magnetic resonance imaging

NUT midline carcinoma – Pathology

Transitional cell carcinoma – Diagnosis | Classification

Large-cell lung carcinoma – Diagnosis

Acinic cell carcinoma – Treatment

Invasive carcinoma of no special type – Prognosis