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

Logo Beuth University of Applied Sciences Berlin

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

Imprint / Contact

Results for Query ‹ Occult pneumonia risk

Hospital-acquired pneumonia – Types | Healthcare-associated pneumonia (HCAP) | Epidemiology

Community-acquired pneumonia – Epidemiology

Hospital-acquired pneumonia – Types | Healthcare-associated pneumonia (HCAP) | Nursing home-acquired pneumonia

Pneumonia – Diagnosis | Classification | Community

Pleural empyema – Epidemiology

Atypical pneumonia – Cause | Viral

Atypical pneumonia – Cause

Lower respiratory tract infection – Pneumonia

Pneumonia – Cause | Bacteria

Community-acquired pneumonia – Causes | Adults

Lower respiratory tract infection – Epidemiology

Klebsiella pneumonia – Pathophysiology | Resistant strains

Pneumocystis pneumonia – Epidemiology | PCP and AIDS

Klebsiella pneumonia – Pathophysiology

Pleural empyema – Prognosis

Aspiration pneumonia – Causes | Risk factors

Pneumocystis pneumonia – Epidemiology

Aspiration pneumonia – Causes | Implicated bacteria

Bacterial pneumonia – Types | Gram-negative

Bacterial pneumonia – Treatment | Atypical organisms

Occult pneumonia – Abstract

Pneumonia (non-human) – Abstract

Lobar pneumonia – Abstract

Lobar pneumonia – Stages

Pneumococcal pneumonia – Abstract