Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium

no code implementations • 3 Mar 2024 • Hyewon Jeong, Sarah Jabbour, Yuzhe Yang, Rahul Thapta, Hussein Mozannar, William Jongwon Han, Nikita Mehandru, Michael Wornow, Vladislav Lialin, Xin Liu, Alejandro Lozano, Jiacheng Zhu, Rafal Dariusz Kocielnik, Keith Harrigian, Haoran Zhang, Edward Lee, Milos Vukadinovic, Aparna Balagopalan, Vincent Jeanselme, Katherine Matton, Ilker Demirel, Jason Fries, Parisa Rashidi, Brett Beaulieu-Jones, Xuhai Orson Xu, Matthew McDermott, Tristan Naumann, Monica Agrawal, Marinka Zitnik, Berk Ustun, Edward Choi, Kristen Yeom, Gamze Gursoy, Marzyeh Ghassemi, Emma Pierson, George Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo

The organization of the research roundtables at the conference involved 17 Senior Chairs and 19 Junior Chairs across 11 tables.

Deep Sequential Learning for Cervical Spine Fracture Detection on Computed Tomography Imaging

no code implementations • 26 Oct 2020 • Hojjat Salehinejad, Edward Ho, Hui-Ming Lin, Priscila Crivellaro, Oleksandra Samorodova, Monica Tafur Arciniegas, Zamir Merali, Suradech Suthiphosuwan, Aditya Bharatha, Kristen Yeom, Muhammad Mamdani, Jefferson Wilson, Errol Colak

Fractures of the cervical spine are a medical emergency and may lead to permanent paralysis and even death.

Computed Tomography (CT) Fracture detection +1