Dataset: 9.3K articles from Wikipedia (CC BY-SA).
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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 ‹ Mycobacterium fortuitum risk

Mycobacterium fortuitum – Abstract

Mycobacterium fortuitum – Treatment

Extensively drug-resistant tuberculosis – Epidemiology

Extensively drug-resistant tuberculosis – XDR-TB and HIV/AIDS

Mycobacterium avium-intracellulare infection – Treatment | HIV-infected children

Mycobacterium avium-intracellulare infection – Cause | Risk factors

Multi-drug-resistant tuberculosis – Epidemiology

Opportunistic infection – Causes

Opportunistic infection – Veterinary treatment

Multiple drug resistance – Abstract

Multiple drug resistance – Common multidrug-resistant organisms (MDROs)

Tuberculosis in relation to HIV – Research at molecular level

Multi-drug-resistant tuberculosis – Epidemiology | Russian prisons | Contributing factors

Miliary tuberculosis – Prognosis

Tuberculosis – Causes | Risk factors

Tuberculosis – Prognosis

Paratuberculosis – Human risks

Tuberculosis in relation to HIV – Prevention

Buruli ulcer – Epidemiology | Race, age and sex

Paratuberculosis – Morbidity and mortality

Subclinical infection – Infection transmission/signs

Buruli ulcer – Epidemiology | Geographical distribution

Miliary tuberculosis – Signs and symptoms

Subclinical infection – Host tolerance

Ghon's complex – Abstract