The project brings together clinicians, biomedical engineers, physiotherapists, computational and social scientists aiming to use innovative approaches to improve the care of critically ill patients in low and middle income settings, focusing on diseases which cause significant morbidity and mortality.
The project aims to use state-of-the-art ways to enhance diagnosis and treatment utilizing machine learning, novel technologies and computational science in 4 specific diseases: sepsis, dengue, tetanus and tuberculous meningitis, using low-cost tools that are suitable use in the management of other life-threatening conditions and for scale-up and use in a wider setting. Read more
Learning meaningful latent space representations for patient risk stratification: Model development and validation for dengue and other acute febrile illness
Bernard Hernandez, Oliver Stiff, Damien K. Ming, and 16 more authors
@article{10.3389/fdgth.2023.1057467,author={Hernandez, Bernard and Stiff, Oliver and Ming, Damien K. and Ho Quang, Chanh and Nguyen Lam, Vuong and Nguyen Minh, Tuan and Nguyen Van Vinh, Chau and Nguyen Minh, Nguyet and Nguyen Quang, Huy and Phung Khanh, Lam and Dong Thi Hoai, Tam and Dinh The, Trung and Huynh Trung, Trieu and Wills, Bridget and Simmons, Cameron P. and Holmes, Alison H. and Yacoub, Sophie and Georgiou, Pantelis and Consortium, VITAL},title={Learning meaningful latent space representations for patient risk stratification: Model development and validation for dengue and other acute febrile illness},journal={Frontiers in Digital Health},volume={5},month=feb,year={2023},doi={10.3389/fdgth.2023.1057467},issn={2673-253X},url={https://www.frontiersin.org/articles/10.3389/fdgth.2023.1057467},dimensions={true}}
@article{nguyen2023mapping,title={Mapping patient pathways and understanding clinical decision-making in dengue management to inform the development of digital health tools},author={Nguyen, Quang Huy and Ming, Damien K and Luu, An Phuoc and Chanh, Ho Quang and Tam, Dong Thi Hoai and Truong, Nguyen Thanh and Huy, Vo Xuan and Hernandez, Bernard and Van Nuil, Jennifer Ilo and Paton, Chris and others},journal={BMC Medical Informatics and Decision Making},volume={23},number={1},pages={24},month=feb,year={2023},publisher={Springer},doi={10.1186/s12911-023-02116-4},url={https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-023-02116-4},}
@article{ming2022diagnosis,title={The Diagnosis of Dengue in Patients Presenting With Acute Febrile Illness Using Supervised Machine Learning and Impact of Seasonality},author={Ming, Damien K and Tuan, Nguyen M and Hernandez, Bernard and Sangkaew, Sorawat and Vuong, Nguyen L and Chanh, Ho Q and Chau, Nguyen VV and Simmons, Cameron P and Wills, Bridget and Georgiou, Pantelis and others},journal={Frontiers in Digital Health},volume={4},date={2022-03-14},year={2022},month=mar,publisher={Frontiers Media SA},doi={10.3389/fdgth.2022.849641},url={},}
@article{ming2022applied,author={Ming, Damien K and Hernandez, Bernard and Sangkaew, Sorawat and Vuong, Nguyen Lam and Lam, Phung Khanh and Nguyet, Nguyen Minh and Tam, Dong Thi Hoai and Trung, Dinh The and Tien, Nguyen Thi Hanh and Tuan, Nguyen Minh and others},journal={PLOS Digital Health},volume={1},number={1},pages={e0000005},date={2022-01-18},year={2022},month=jan,publisher={Public Library of Science San Francisco, CA USA},doi={10.1371/journal.pdig.0000005},url={},dimensions={true}}