Jacob, Joseph

Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans

Roberts, M., Driggs, D., Thorpe, M., Gilbey, J., Yeung, M., Ursprung, S., Aviles-Rivero, A. I., Etmann, C., McCague, C., Beer, L., et al. (2021) · Nature Machine Intelligence

COVID-19 diagnosis using AIArtificial Intelligence in Healthcare and Education

Cited by 1,044

‘Long-COVID’: a cross-sectional study of persisting symptoms, biomarker and imaging abnormalities following hospitalisation for COVID-19

Mandal, S., Barnett, J., Brill, S. E., Brown, J. S., Denneny, E. K., Hare, S. S., Heightman, M., Hillman, T. E., Jacob, J., Jarvis, H. C., et al. (2021) · Thorax

Long-Term Effects of COVID-19COVID-19 Clinical Research Studies

Cited by 864

Mortality prediction in idiopathic pulmonary fibrosis: evaluation of computer-based CT analysis with conventional severity measures

Jacob, J., Bartholmai, B. J., Rajagopalan, S., Kokosi, M., Nair, A., Karwoski, R., Walsh, S. L. F., Wells, A. U., & Hansell, D. M. (2017) · European Respiratory Journal

Interstitial Lung Diseases and Idiopathic Pulmonary FibrosisOccupational and environmental lung diseases

Cited by 309

Predicting outcomes in idiopathic pulmonary fibrosis using automated computed tomographic analysis

Jacob, J., Bartholmai, B. J., Rajagopalan, S., van Moorsel, C. H. M., van Es, H. W., van Beek, F. T., Struik, M. H. L., Kokosi, M., Egashira, R., Brun, A. L., et al. (2018) · American Journal of Respiratory and Critical Care Medicine

Interstitial Lung Diseases and Idiopathic Pulmonary FibrosisChronic Obstructive Pulmonary Disease (COPD) Research

Cited by 198

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

Yildirim, N., Richardson, H., Wetscherek, M. T., Bajwa, J., Jacob, J., Pinnock, M. A., Harris, S., Coelho De Castro, D., Bannur, S., Hyland, S., et al. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 82

Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology

Thieme, A., Rajamohan, A., Cooper, B., Groombridge, H., Simister, R., Wong, B., Woznitza, N., Pinnock, M. A., Wetscherek, M. T., Morrison, C., et al. (2024) · arXiv

Artificial Intelligence in Healthcare and EducationExplainable Artificial Intelligence (XAI)

Cited by 10