| Whole-genome sequencing for prediction of Mycobacterium tuberculosis drug susceptibility and resistance: a retrospective cohort study TM Walker, TA Kohl, SV Omar, J Hedge, CDO Elias, P Bradley, Z Iqbal, ... The Lancet infectious diseases 15 (10), 1193-1202, 2015 | 653* | 2015 |
| Machine learning and decision support in critical care AEW Johnson, MM Ghassemi, S Nemati, KE Niehaus, DA Clifton, ... Proceedings of the IEEE 104 (2), 444-466, 2016 | 390 | 2016 |
| Machine learning and decision support in critical care AEW Johnson, MM Ghassemi, S Nemati, KE Niehaus, DA Clifton, ... Proceedings of the IEEE 104 (2), 444-466, 2016 | 390 | 2016 |
| Risk of cardiovascular disease from antiretroviral therapy for HIV: a systematic review C Bavinger, E Bendavid, K Niehaus, RA Olshen, I Olkin, V Sundaram, ... PloS one 8 (3), e59551, 2013 | 263 | 2013 |
| Machine learning enables detection of early-stage colorectal cancer by whole-genome sequencing of plasma cell-free DNA N Wan, D Weinberg, TY Liu, K Niehaus, EA Ariazi, D Delubac, A Kannan, ... BMC cancer 19, 1-10, 2019 | 136 | 2019 |
| Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data Y Yang, KE Niehaus, TM Walker, Z Iqbal, AS Walker, DJ Wilson, TEA Peto, ... Bioinformatics 34 (10), 1666-1671, 2018 | 116 | 2018 |
| First steps in using machine learning on fMRI data to predict intrusive memories of traumatic film footage IA Clark, KE Niehaus, EP Duff, MC Di Simplicio, GD Clifford, SM Smith, ... Behaviour research and therapy 62, 37-46, 2014 | 58 | 2014 |
| Health informatics via machine learning for the clinical management of patients DA Clifton, KE Niehaus, P Charlton, GW Colopy Yearbook of medical informatics 24 (01), 38-43, 2015 | 55 | 2015 |
| Machine learning for the prediction of antibacterial susceptibility in Mycobacterium tuberculosis KE Niehaus, TM Walker, DW Crook, TEA Peto, DA Clifton IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI …, 2014 | 42 | 2014 |
| Machine learning implementation for multi-analyte assay development and testing A Drake, D Delubac, K Niehaus, E Ariazi, I Haque, TY Liu, N Wan, ... US Patent 11,681,953, 2023 | 14 | 2023 |
| Phenotypic characterisation of Crohn's disease severity KE Niehaus, HH Uhlig, DA Clifton 2015 37th Annual International Conference of the IEEE Engineering in …, 2015 | 8 | 2015 |
| MVPA to enhance the study of rare cognitive events: An investigation of experimental PTSD KE Niehaus, IA Clark, C Bourne, CE Mackay, EA Holmes, SM Smith, ... 2014 International Workshop on Pattern Recognition in Neuroimaging, 1-4, 2014 | 8 | 2014 |
| Machine learning implementation for multi-analyte assay development and testing A Drake, D Delubac, K Niehaus, E Ariazi, I Haque, TY Liu, N Wan, ... US Patent 11,847,532, 2023 | 5 | 2023 |
| Contributions from the 2019 literature on bioinformatics and translational informatics M Smaïl-Tabbone, B Rance Yearbook of Medical Informatics 29 (01), 188-192, 2020 | 4 | 2020 |
| Patient-specific physiological monitoring and prediction using structured Gaussian processes T Zhu, GW Colopy, C Macewen, K Niehaus, Y Yang, CW Pugh, DA Clifton IEEE Access 7, 58094-58103, 2019 | 4 | 2019 |
| Machine learning for chronic disease KE Niehaus, DA Clifton Machine Learning for Healthcare Technologies 2, 227, 2016 | 3 | 2016 |
| Predicting antibiotic resistance from genomic data Y Yang, KE Niehaus, DA Clifton Machine learning for healthcare technologies, 203-226, 0 | 3 | |
| Intelligent electronic health systems DA Clifton, MAF Pimentel, KE Niehaus, L Clifton, TEA Peto, DW Crook, ... Telemedicine and electronic medicine, 73-97, 2018 | 2 | 2018 |
| Phenotypic modelling of Crohn's disease severity: a machine learning approach K Niehaus University of Oxford, 2016 | 2 | 2016 |
| Kohl Th. A., Omar Sh. V., Hedge J. et al. Whole-genome sequencing for prediction of Mycobacterium tuberculosis drug susceptibility and resistance: a retrospective cohort study TM Walker Lancet Infect. Dis 15, 1193-1202, 2015 | 2 | 2015 |
