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 ‹ Epithelial-myoepithelial carcinoma screening

Carcinoma – Epidemiology

Carcinoma – Diagnosis

Epithelial-myoepithelial carcinoma of the lung – Prognosis and Survival

Epithelial-myoepithelial carcinoma – Prognosis

Salivary gland tumour – Diagnosis

Epithelial-myoepithelial carcinoma of the lung – Staging

Pleomorphic adenoma – Diagnosis

Urachal cancer – Diagnosis

Transitional cell carcinoma – Diagnosis | Classification

Surface epithelial-stromal tumor – Metastases

Mucinous cystadenocarcinoma of the lung – Prognosis and Survival

Lobular carcinoma in situ – Prognosis

Myoepithelioma of the head and neck – Treatment

Urachal cancer – Histopathology

Primary peritoneal carcinoma – Prognosis and treatment

Metanephric adenoma – Treatment

Signet ring cell carcinoma – Prognosis by organ

Mucinous cystadenocarcinoma of the lung – Treatment

Epithelial-myoepithelial carcinoma – Diagnosis

Epithelioma – Prognosis

Bladder cancer in cats and dogs – Diagnosis

Surface epithelial-stromal tumor – Treatment

Epithelioma – Treatment

NUT midline carcinoma – Pathology

Salivary gland tumour – Treatment