Computer-aided prognosis of tuberculous meningitis combining imaging and non-imaging data

Journal article

Tuberculous meningitis (TBM) is the most lethal form of tuberculosis. Clinical features, such as coma, can predict death, but they are insufficient for the accurate prognosis of other outcomes, especially when impacted by co-morbidities such as HIV infection. Brain magnetic resonance imaging (MRI) characterises the extent and severity of disease and may enable more accurate prediction of complications and poor outcomes. We analysed clinical and brain MRI data from a prospective longitudinal s...

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Authors: Canas, LS; Dong, THK; Beasley, D; Donovan, J; Cleary, JO

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Nature Research
• Journal: Scientific Reports
• Volume: 14
• Issue: 1
• Article number: 17581
• Publication date: 2024-07-30
• Acceptance date: 2024-07-22
• DOI: 10.1038/s41598-024-68308-8
• EISSN: 2045-2322
• ISSN: 2045-2322
• Language: English
• Keywords: MRI imaging; Long short-term memory network; Prognosis; DenseNet; Tuberculous meningitis; Machine learning