Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Jeanselme, Vincent"'
Identifying patient subgroups with different treatment responses is an important task to inform medical recommendations, guidelines, and the design of future clinical trials. Existing approaches for subgroup analysis primarily focus on Randomised Con
Externí odkaz:
http://arxiv.org/abs/2408.03463
Autor:
Jeong, Hyewon, Jabbour, Sarah, Yang, Yuzhe, Thapta, Rahul, Mozannar, Hussein, Han, William Jongwon, Mehandru, Nikita, Wornow, Michael, Lialin, Vladislav, Liu, Xin, Lozano, Alejandro, Zhu, Jiacheng, Kocielnik, Rafal Dariusz, Harrigian, Keith, Zhang, Haoran, Lee, Edward, Vukadinovic, Milos, Balagopalan, Aparna, Jeanselme, Vincent, Matton, Katherine, Demirel, Ilker, Fries, Jason, Rashidi, Parisa, Beaulieu-Jones, Brett, Xu, Xuhai Orson, McDermott, Matthew, Naumann, Tristan, Agrawal, Monica, Zitnik, Marinka, Ustun, Berk, Choi, Edward, Yeom, Kristen, Gursoy, Gamze, Ghassemi, Marzyeh, Pierson, Emma, Chen, George, Kanjilal, Sanjat, Oberst, Michael, Zhang, Linying, Singh, Harvineet, Hartvigsen, Tom, Zhou, Helen, Okolo, Chinasa T.
The third ML4H symposium was held in person on December 10, 2023, in New Orleans, Louisiana, USA. The symposium included research roundtable sessions to foster discussions between participants and senior researchers on timely and relevant topics for
Externí odkaz:
http://arxiv.org/abs/2403.01628
Time-to-event modelling, known as survival analysis, differs from standard regression as it addresses censoring in patients who do not experience the event of interest. Despite competitive performances in tackling this problem, machine learning metho
Externí odkaz:
http://arxiv.org/abs/2305.06703
Machine learning risks reinforcing biases present in data, and, as we argue in this work, in what is absent from data. In healthcare, biases have marked medical history, leading to unequal care affecting marginalised groups. Patterns in missing data
Externí odkaz:
http://arxiv.org/abs/2208.06648
Autor:
Jeanselme, Vincent, Martin, Glen, Peek, Niels, Sperrin, Matthew, Tom, Brian, Barrett, Jessica
Observational data in medicine arise as a result of the complex interaction between patients and the healthcare system. The sampling process is often highly irregular and itself constitutes an informative process. When using such data to develop pred
Externí odkaz:
http://arxiv.org/abs/2205.13481
Clustering under pairwise constraints is an important knowledge discovery tool that enables the learning of appropriate kernels or distance metrics to improve clustering performance. These pairwise constraints, which come in the form of must-link and
Externí odkaz:
http://arxiv.org/abs/2203.12546
Machine learning (ML) is increasingly being used to support high-stakes decisions. However, there is frequently a construct gap: a gap between the construct of interest to the decision-making task and what is captured in proxies used as labels to tra
Externí odkaz:
http://arxiv.org/abs/2101.09648
Publikováno v:
Advances in Data Analysis & Classification; Jun2024, Vol. 18 Issue 2, p309-324, 16p
Survival analysis involves the modelling of the times to event. Proposed neural network approaches maximise the predictive performance of traditional survival models at the cost of their interpretability. This impairs their applicability in high stak
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d9d88a6b3e39556b1c5b5d85a2a4a935
https://www.repository.cam.ac.uk/handle/1810/336005
https://www.repository.cam.ac.uk/handle/1810/336005
Autor:
Yoon, Joo Heung, Jeanselme, Vincent, Dubrawski, Artur, Hravnak, Marilyn, Pinsky, Michael R., Clermont, Gilles
Additional file 6: Table S1. Demographic and clinical characteristics of training and validation cohorts.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1772eb6729da712dfb63017ed4cc2409