A5101857466- COVID-19 diagnosis using AI
- Machine Learning in Healthcare
- Biomedical Text Mining and Ontologies
- COVID-19 Clinical Research Studies
- Ear Surgery and Otitis Media
- Chronic Disease Management Strategies
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 and healthcare impacts
- Topic Modeling
- Hearing Impairment and Communication
- Bioinformatics and Genomic Networks
- Artificial Intelligence in Healthcare and Education
- Semantic Web and Ontologies
- Hearing Loss and Rehabilitation
- Frailty in Older Adults
- Health Systems, Economic Evaluations, Quality of Life
- Renaissance Literature and Culture
- Lung Cancer Diagnosis and Treatment
- Health disparities and outcomes
- Names, Identity, and Discrimination Research
NHS England
2023-2024
NHS Digital
2021-2024
The prevalence of the coronavirus SARS-CoV-2 disease has resulted in unprecedented collection health data to support research. Historically, coordinating collation such datasets on a national scale been challenging execute for several reasons, including issues with privacy, lack reporting standards, interoperable technologies, and distribution methods. pandemic highlighted importance collaboration between government bodies, healthcare institutions, academic researchers commercial companies...
Download This Paper Open PDF in Browser Add to My Library Share: Permalink Using these links will ensure access this page indefinitely Copy URL DOI
Abstract The COVID-19 pandemic has been a great challenge to healthcare systems worldwide. It highlighted the need for robust predictive models which can be readily deployed uncover heterogeneities in disease course, aid decision-making and prioritise treatment. We adapted an unsupervised data-driven model—SuStaIn, utilised short-term infectious like COVID-19, based on 11 commonly recorded clinical measures. used 1344 patients from National Chest Imaging Database (NCCID), hospitalised RT-PCR...
Abstract Objective To introduce directed hypergraphs as a novel tool for assessing the temporal relationships between coincident diseases, addressing need more accurate representation of multimorbidity and leveraging growing availability electronic healthcare databases improved computational resources. Methods Directed offer high-order analytical framework that goes beyond limitations graphs in representing complex such multimorbidity. We apply this approach to multimorbid disease...
Abstract The National COVID-19 Chest Imaging Database (NCCID) is a centralised database containing chest X-rays, Computed Tomography (CT) scans and cardiac Magnetic Resonance Images (MRI) from patients across the UK, jointly established by NHSX, British Society of Thoracic (BSTI), Royal Surrey NHS Foundation Trust (RSNFT) Faculty. objective initiative to support better understanding coronavirus SARS-CoV-2 disease (COVID-19) development machine learning (ML) technologies that will improve...
Objective: To introduce directed hypergraphs as a novel tool for assessing the temporal relationships between coincident diseases, addressing need more accurate representation of multimorbidity and leveraging growing availability electronic healthcare databases improved computational resources.Methods: Directed offer high-order analytical framework that goes beyond limitations graphs in representing complex such multimorbidity. We apply this approach to multimorbid disease progressions...