Search Results - "Philipsen RHHM"

Meta-analysis of quantum convolutional neural networks for automated tuberculosis screening on chest x-rays.

Authors: Rana, Anurag Bhaglani, Dimple Kumar Vaidya, Pankaj et al.

Source: Multimedia Tools & Applications; Oct2025, Vol. 84 Issue 33, p40781-40807, 27p

Tuberculosis detection using deep and hybrid learning techniques using X-ray images.

Authors: Shilpa, N. Ayeesha Banu, W.

Source: Neural Computing & Applications; Jun2025, Vol. 37 Issue 18, p12373-12406, 34p

Diagnostic Accuracy of Computer-Aided Detection During Active Case Finding for Pulmonary Tuberculosis in Africa: A Systematic Review and Meta-analysis.

Authors: Scott, Alex J Perumal, Tahlia Hohlfeld, Ameer et al.

Source: Open Forum Infectious Diseases. Feb2024, Vol. 11 Issue 2, p1-9. 9p.

Diagnostic Performance of Artificial Intelligence–Based Methods for Tuberculosis Detection: Systematic Review.

Authors: Hansun, Seng Argha, Ahmadreza Bakhshayeshi, Ivan et al.

Source: Journal of Medical Internet Research. 2025, Vol. 27, p1-23. 23p.

Review on chest pathogies detection systems using deep learning techniques.

Authors: Rehman, Arshia Khan, Ahmad Fatima, Gohar et al.

Source: Artificial Intelligence Review; Nov2023, Vol. 56 Issue 11, p12607-12653, 47p

Medical image-based detection of COVID-19 using Deep Convolution Neural Networks.

Authors: Gaur, Loveleen Bhatia, Ujwal Jhanjhi, N. Z. et al.

Source: Multimedia Systems; Jun2023, Vol. 29 Issue 3, p1729-1738, 10p

HIV, multimorbidity, and health-related quality of life in rural KwaZulu-Natal, South Africa: A population-based study.

Authors: Stanton, Amelia M. Boyd, Ryan L. O'Cleirigh, Conall et al.

Source: PLoS ONE. 2/21/2024, Vol. 19 Issue 2, p1-21. 21p.

Applicability of artificial intelligence-based computer-aided detection (AI–CAD) for pulmonary tuberculosis to community-based active case finding.

Authors: Okada, Kosuke Yamada, Norio Takayanagi, Kiyoko et al.

Source: Tropical Medicine & Health. 1/2/2024, Vol. 52 Issue 1, p1-10. 10p.

A lightweight deep learning architecture for the automatic detection of pneumonia using chest X-ray images.

Authors: Trivedi, Megha Gupta, Abhishek

Source: Multimedia Tools & Applications; Feb2022, Vol. 81 Issue 4, p5515-5536, 22p

Alarming Tuberculosis Rate Among People Who Inject Drugs in Vietnam.

Authors: Nagot, Nicolas Hai, Vinh Vu Dong, Thuy Thi Thu et al.

Source: Open Forum Infectious Diseases. Feb2022, Vol. 9 Issue 2, p1-7. 7p.

Self-supervised learning framework application for medical image analysis: a review and summary.

Authors: Zeng, Xiangrui Abdullah, Nibras Sumari, Putra

Source: BioMedical Engineering OnLine. 10/27/2024, Vol. 23 Issue 1, p1-36. 36p.

Triage of Persons With Tuberculosis Symptoms Using Artificial Intelligence–Based Chest Radiograph Interpretation: A Cost-Effectiveness Analysis.

Authors: Nsengiyumva, Ntwali Placide Hussain, Hamidah Oxlade, Olivia et al.

Source: Open Forum Infectious Diseases. Dec2021, Vol. 8 Issue 12, p1-11. 11p.

Evaluating the yield of systematic screening for tuberculosis among three priority groups in Ho Chi Minh City, Viet Nam.

Authors: Vo, Luan Nguyen Quang Codlin, Andrew James Forse, Rachel Jeanette et al.

Source: Infectious Diseases of Poverty. 12/9/2020, Vol. 9 Issue 1, p1-13. 13p.

Evaluation of the diagnostic accuracy of Computer-Aided Detection of tuberculosis on Chest radiography among private sector patients in Pakistan.

Authors: Zaidi, Syed Mohammad Asad Habib, Shifa Salman Van Ginneken, Bram et al.

Source: Scientific Reports. 8/17/2018, Vol. 8 Issue 1, p1-8. 8p.

Machine and Deep Learning for Tuberculosis Detection on Chest X-Rays: Systematic Literature Review.

Authors: Hansun, Seng Argha, Ahmadreza Liaw, Siaw-Teng et al.

Source: Journal of Medical Internet Research. 2023, Vol. 25 Issue 1, p1-22. 22p.

Cost and affordability of scaling up tuberculosis diagnosis using Xpert MTB/RIF testing in West Java, Indonesia.

Authors: Nadjib, Mardiati Dewi, Retno Kusuma Setiawan, Ery et al.

Source: PLoS ONE. 3/10/2022, Vol. 17 Issue 3, p1-16. 16p.

Deep learning-based automatic detection of tuberculosis disease in chest X-ray images.

Authors: Showkatian, Eman Salehi, Mohammad Ghaffari, Hamed et al.

Source: Polish Journal of Radiology. 2022, Vol. 87 Issue 1, pe118-e124. 7p.

Artificial intelligence with deep learning in nuclear medicine and radiology.

Authors: Decuyper, Milan Maebe, Jens Van Holen, Roel et al.

Source: EJNMMI Physics. 12/11/2021, Vol. 8 Issue 1, p1-46. 46p.

Anatomic Point–Based Lung Region with Zone Identification for Radiologist Annotation and Machine Learning for Chest Radiographs.

Authors: Li, Feng Armato, Samuel G. Engelmann, Roger et al.

Source: Journal of Digital Imaging; Aug2021, Vol. 34 Issue 4, p922-931, 10p, 3 Black and White Photographs, 3 Diagrams, 2 Charts

A systematic review of the diagnostic accuracy of artificial intelligence-based computer programs to analyze chest x-rays for pulmonary tuberculosis.

Authors: Harris, Miriam Qi, Amy Jeagal, Luke et al.

Source: PLoS ONE. 9/2/2019, Vol. 14 Issue 9, p1-19. 19p.