Research output per year
Research output per year
Personal profile
Biographical details
Giovanni Montana is Professor of Biostatistics and Bionformatics in the Department of Biomedical Engineering at King's College London. He received a Ph.D. in Statistics from the University of Warwick in 2003, and then held a post-doctoral position at the University of Chicago. In 2004 he joined the Statistical Genetics & Biomarkers research group at Bristol-Myers Squibb, in Princeton. Prior to joining King's College in 2013, he was Reader (Associate Professor) in Statistics in the Department of Mathematics at Imperial College London, which he joined in 2005 as GlaxosmithKline Lecturer in Statistics. He's a Fellow of the Royal Statistical Society and Chartered Statistician, and holds a Visiting Professor position in the Department of Mathematics at Imperial College. His main research interests lie in statistical computing and machine learning with applications to biomedical data analysis, including genomic and medical imaging. He's also actively working in Big Data analytics.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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Collaborations and top research areas from the last five years
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Patient Reidentification from Chest Radiographs: AInterpretable Deep Metric Learning Approach and Its Applications
MacPherson, M., Hutchinson, C., Horst, C., Goh, V. & Montana, G., Nov 2023, In: Radiology: Artificial intelligence. 5, 6, e230019.Research output: Contribution to journal › Article › peer-review
Open Access1 Citation (Scopus) -
A persistent homology-based topological loss for CNN-based multi-class segmentation of CMR
Byrne, N., Clough, J. R., Valverde, I., Montana, G. & King, A. P., 31 Aug 2022, (E-pub ahead of print) In: IEEE Transactions on Medical Imaging. PPResearch output: Contribution to journal › Article › peer-review
Open Access7 Citations (Scopus) -
Assessing the Performance of Automated Prediction and Ranking of Patient Age from Chest X-rays Against Clinicians
MacPherson, M., Muthuswamy, K., Amlani, A., Hutchinson, C., Goh, V. & Montana, G., 17 Sept 2022, Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 - 25th International Conference, Proceedings. Wang, L., Dou, Q., Fletcher, P. T., Speidel, S. & Li, S. (eds.). Springer Science and Business Media Deutschland GmbH, p. 255-265 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13437 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
1 Citation (Scopus) -
Parental Education and Youth Suicidal Behaviors: A Systematic Review and Meta-Analysis
Chen, P. J., MacKes, N., Sacchi, C., Lawrence, A., Ma, X., Pollard, R., Matter, M., Morgan, C., Harding, S., Schumann, G., Pariante, C., Mehta, M., Montana, G., Nosarti, C. & Dazzan, P., 7 Feb 2022, (Accepted/In press) In: Epidemiology and Psychiatric Sciences.Research output: Contribution to journal › Article › peer-review
Open AccessFile46 Downloads (Pure) -
A Persistent Homology-Based Topological Loss Function for Multi-class CNN Segmentation of Cardiac MRI
Byrne, N., Clough, J. R., Montana, G. & King, A. P., 2021, Statistical Atlases and Computational Models of the Heart. MandMs and EMIDEC Challenges - 11th International Workshop, STACOM 2020, Held in Conjunction with MICCAI 2020, Revised Selected Papers. Puyol Anton, E., Pop, M., Sermesant, M., Campello, V., Lalande, A., Lekadir, K., Suinesiaputra, A., Camara, O. & Young, A. (eds.). Springer Science and Business Media Deutschland GmbH, p. 3-13 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12592 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
13 Citations (Scopus)
Projects
- 19 Finished
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FaCE (Facial Characteristics and Epigenetics): Machine Learning for Fully-automated 3D Face Phenotyping and Epigenetic Analysis
4/02/2018 → 3/02/2021
Project: Research
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Combining phone-based ecological momentary assessment and supervised machine learning to predict psychotic relapse at the individual level
1/01/2018 → 31/12/2019
Project: Research
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PIC - Personalised In-Silico Cardiology
Lamata de la Orden, P., Niederer, S., Eckersley, R., Nordsletten, D. & Montana, G.
1/09/2017 → 31/08/2021
Project: Research
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PROGRESS: Distinguishing fake progression from real tumour growth
1/04/2017 → 31/03/2020
Project: Research