Global tuberculosis report (2014)

By L. Gabbasova, E. Who. 2014

6,191 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/5f803ccfc7014ce2a5290aed29966ec7d312c8a1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Muhammad Enamul Hoque Chowdhury
2. Tawsifur Rahman
3. A. Havelaar
4. M. Kirk
5. P. Torgerson
6. Amith Abdullah Khandakar
7. J. Wolf
8. A. Prüss-Ustün

Citations in the corpus

• Crystal structure of the putative cell-wall lipoglycan biosynthesis protein LmcA from Mycobacterium smegmatis (2022, background): “M. tuberculosis infects around one-quarter of the entire human population and causes approximately 1.4 million deaths annually, making it one of the top ten causes of death worldwide (World Health Organization, 2020).”
• Computer-aided detection in chest radiography based on artificial intelligence: a survey (2018, background): “Globally, in 2016, the proportion of people who developed TB and died from the disease (case fatality ratio, CFR) was 16%, which meant that an estimated 10.4 million people (90% adults; 65% male; 10% people living with HIV) fell ill with TB [78].”
• Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019 (2020, background): “41 The prominent rankings of COPD and lung cancer in the 50–74-year and 75-years-and-older age groups emphasise the continuing need for tobacco-control measures and attention to reducing exposure to indoor and outdoor air pollution.”
• Detection (2020, unknown): “Real-time communications (RTC) have experienced an unprecedented development and consolidated their position as indispensable tools in recent years, supporting services such as videoconferencing, streaming, and online gaming, to play a profound role in remote work, recreation, education, and beyond.”
• Reliable Tuberculosis Detection Using Chest X-Ray With Deep Learning, Segmentation and Visualization (2020, background): “[1] WHO, "Global tuberculosis report 2019," 2019.”
• Preventing disease through healthy environments: a global assessment of the burden of disease from environmental risks (2016, background): “…measures and other traffic control solutions; separation of pedestrians from motorized traffic etc. Housing/community • Household air pollution: use of clean fuels; strategies to reduce exposure to smoke from solid fuels – implementation of WHO Indoor Air Quality Guidelines (WHO, 2014ee).”
• World Health Organization Estimates of the Global and Regional Disease Burden of 22 Foodborne Bacterial, Protozoal, and Viral Diseases, 2010: A Data Synthesis (2015, methodology): “To derive estimates of human M . bovis incidence, we multiplied WHO country-specific human TB incidence by the estimate of the proportion of human TB infections that were due to M . bovis [45].”