Zobrazeno 1 - 10
of 269
pro vyhledávání: '"Olivier Gevaert"'
Autor:
Marija Pizurica, Yuanning Zheng, Francisco Carrillo-Perez, Humaira Noor, Wei Yao, Christian Wohlfart, Antoaneta Vladimirova, Kathleen Marchal, Olivier Gevaert
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-14 (2024)
Abstract Cancer is a heterogeneous disease requiring costly genetic profiling for better understanding and management. Recent advances in deep learning have enabled cost-effective predictions of genetic alterations from whole slide images (WSIs). Whi
Externí odkaz:
https://doaj.org/article/d5a28a5c4a814a67a178ded2609934fa
Autor:
Jill M. Brooks, Yuanning Zheng, Kelly Hunter, Benjamin E. Willcox, Janet Dunn, Paul Nankivell, Olivier Gevaert, Hisham Mehanna
Publikováno v:
Frontiers in Oncology, Vol 14 (2024)
BackgroundThe incidence of oropharyngeal cancer (OPC) is increasing, due mainly to a rise in Human Papilloma Virus (HPV)-mediated disease. HPV-mediated OPC has significantly better prognosis compared with HPV-negative OPC, stimulating interest in tre
Externí odkaz:
https://doaj.org/article/f12a3ff832bb48f7a7eb35b9911523e9
Autor:
Ahmet Gorkem Er, Daisy Yi Ding, Berrin Er, Mertcan Uzun, Mehmet Cakmak, Christoph Sadee, Gamze Durhan, Mustafa Nasuh Ozmen, Mine Durusu Tanriover, Arzu Topeli, Yesim Aydin Son, Robert Tibshirani, Serhat Unal, Olivier Gevaert
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-11 (2024)
Abstract Through technological innovations, patient cohorts can be examined from multiple views with high-dimensional, multiscale biomedical data to classify clinical phenotypes and predict outcomes. Here, we aim to present our approach for analyzing
Externí odkaz:
https://doaj.org/article/60405c4434f3445781f9660de29169a1
Foundation metrics for evaluating effectiveness of healthcare conversations powered by generative AI
Autor:
Mahyar Abbasian, Elahe Khatibi, Iman Azimi, David Oniani, Zahra Shakeri Hossein Abad, Alexander Thieme, Ram Sriram, Zhongqi Yang, Yanshan Wang, Bryant Lin, Olivier Gevaert, Li-Jia Li, Ramesh Jain, Amir M. Rahmani
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-14 (2024)
Abstract Generative Artificial Intelligence is set to revolutionize healthcare delivery by transforming traditional patient care into a more personalized, efficient, and proactive process. Chatbots, serving as interactive conversational models, will
Externí odkaz:
https://doaj.org/article/7200320f40114efc894e8403816b5323
Autor:
Chuanjun Xu, Qinmei Xu, Li Liu, Mu Zhou, Zijian Xing, Zhen Zhou, Danyang Ren, Changsheng Zhou, Longjiang Zhang, Xiao Li, Xianghao Zhan, Olivier Gevaert, Guangming Lu
Publikováno v:
European Journal of Radiology Open, Vol 13, Iss , Pp 100603- (2024)
Purpose: The novel coronavirus pneumonia (COVID-19) has continually spread and mutated, requiring a patient risk stratification system to optimize medical resources and improve pandemic response. We aimed to develop a conformal prediction-based tri-l
Externí odkaz:
https://doaj.org/article/c18272aff51b4df1a687f4c510bb6b87
Autor:
Akshay Swaminathan, Iván López, Rafael Antonio Garcia Mar, Tyler Heist, Tom McClintock, Kaitlin Caoili, Madeline Grace, Matthew Rubashkin, Michael N. Boggs, Jonathan H. Chen, Olivier Gevaert, David Mou, Matthew K. Nock
Publikováno v:
npj Digital Medicine, Vol 6, Iss 1, Pp 1-9 (2023)
Abstract Patients experiencing mental health crises often seek help through messaging-based platforms, but may face long wait times due to limited message triage capacity. Here we build and deploy a machine-learning-enabled system to improve response
Externí odkaz:
https://doaj.org/article/5183d274f50d4c218f6598b4aaaee6cf
Autor:
Kevin Brennan, Almudena Espín-Pérez, Serena Chang, Nikita Bedi, Saumyaa Saumyaa, June Ho Shin, Sylvia K. Plevritis, Olivier Gevaert, John B. Sunwoo, Andrew J. Gentles
Publikováno v:
Genome Medicine, Vol 15, Iss 1, Pp 1-26 (2023)
Abstract Background The prognosis for patients with head and neck cancer (HNC) is poor and has improved little in recent decades, partially due to lack of therapeutic options. To identify effective therapeutic targets, we sought to identify molecular
Externí odkaz:
https://doaj.org/article/64cfbc02ed7142e4ba40972bf22f174f
Autor:
Xianghao Zhan, Yiheng Li, Yuzhe Liu, Nicholas J. Cecchi, Samuel J. Raymond, Zhou Zhou, Hossein Vahid Alizadeh, Jesse Ruan, Saeed Barbat, Stephen Tiernan, Olivier Gevaert, Michael M. Zeineh, Gerald A. Grant, David B. Camarillo
Publikováno v:
Journal of Sport and Health Science, Vol 12, Iss 5, Pp 619-629 (2023)
Background: Traumatic brain injury can be caused by head impacts, but many brain injury risk estimation models are not equally accurate across the variety of impacts that patients may undergo, and the characteristics of different types of impacts are
Externí odkaz:
https://doaj.org/article/334dac0a60b244f79dfcd59cee5d0eca
Autor:
Yuanning Zheng, Francisco Carrillo-Perez, Marija Pizurica, Dieter Henrik Heiland, Olivier Gevaert
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-16 (2023)
Abstract Intra-tumoral heterogeneity and cell-state plasticity are key drivers for the therapeutic resistance of glioblastoma. Here, we investigate the association between spatial cellular organization and glioblastoma prognosis. Leveraging single-ce
Externí odkaz:
https://doaj.org/article/22faf8906d774cada1c4535ae16bc84b
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract We propose an interpretable and scalable model to predict likely diagnoses at an encounter based on past diagnoses and lab results. This model is intended to aid physicians in their interaction with the electronic health records (EHR). To ac
Externí odkaz:
https://doaj.org/article/a789732b1e5b44ad850861d64283428d