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 ‹ Carcinoma of the Ureter risk

Ureteral cancer – Risk factors

Ureteral cancer – Epidemiology

Transitional cell carcinoma – Causes

Primary peritoneal carcinoma – Prognosis and treatment

Invasive urothelial carcinoma – Prognosis and treatment

Lobular carcinoma in situ – Prognosis

Primary peritoneal carcinoma – Genetic causes

Invasive urothelial carcinoma – Abstract

Transitional cell carcinoma – Abstract

Carcinoma – Epidemiology

Clear-cell adenocarcinoma – Abstract

Transitional cell carcinoma of the ovary – Prognosis

Transitional cell carcinoma of the ovary – Abstract

Serous carcinoma – Abstract

Serous carcinoma – Differential diagnosis

Lobular carcinoma in situ – Treatment options

Ureteral neoplasm – Abstract

Squamous cell carcinoma – Types | Lung

Squamous cell carcinoma – Types

Renal medullary carcinoma – Epidemiology

Renal medullary carcinoma – Prognosis

Clear cell carcinoma – Abstract

Epithelial-myoepithelial carcinoma of the lung – Incidence

Epithelial-myoepithelial carcinoma of the lung – Prognosis and Survival

Small-cell carcinoma – Epidemiology