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chore: fix the start and end date of challenge id 535 (CHALLENGE-597) #2974

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Jan 22, 2025
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chore: fix the start and end date of challenge id 535 (CHALLENGE-597) #2974

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2 changes: 1 addition & 1 deletion apps/openchallenges/challenge-service/src/main/resources/db/challenges.csv
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Original file line number Diff line number Diff line change
Expand Up @@ -533,4 +533,4 @@
"532","rsna-2024-lumbar-spine-degenerative-classification","RSNA 2024 Lumbar Spine Degenerative Classification","Classify lumbar spine degenerative conditions","Low back pain is the leading cause of disability worldwide, according to the World Health Organization, affecting 619 million people in 2020. Most people experience low back pain at some point in their lives, with the frequency increasing with age. Pain and restricted mobility are often symptoms of spondylosis, a set of degenerative spine conditions including degeneration of intervertebral discs and subsequent narrowing of the spinal canal (spinal stenosis), subarticular recesses, or neural foramen with associated compression or irritations of the nerves in the low back. Magnetic resonance imaging (MRI) provides a detailed view of the lumbar spine vertebra, discs and nerves, enabling radiologists to assess the presence and severity of these conditions. Proper diagnosis and grading of these conditions help guide treatment and potential surgery to help alleviate back pain and improve overall health and quality of life for patients. RSNA has teamed with the American Society of Neur...","","https://www.kaggle.com/competitions/rsna-2024-lumbar-spine-degenerative-classification","completed","8","","2024-05-16","2024-10-08","2648","2024-12-09 17:12:16","2024-12-09 17:12:24"
"533","leap-atmospheric-physics-ai-climsim","LEAP - Atmospheric Physics using AI (ClimSim)","Simulate higher resolution atmospheric processes within E3SM-MMF.","Climate models are essential to understanding Earth''s climate system. Because of the complexity of Earth''s climate, these models rely on parameterizations to approximate the effects of physical processes that occur at scales smaller than the size of their grid cells. These approximations are imperfect, however, and their imperfections are a leading source of uncertainty in expected warming, changing precipitation patterns, and the frequency and severity of extreme events. The Multi-scale Modeling Framework (MMF) approach, by contrast, more explicitly represents these subgrid processes, but at a cost too high to be used for operational climate prediction. Your task is to develop ML models that emulate subgrid atmospheric processes–such as storms, clouds, turbulence, rainfall, and radiation–within E3SM-MMF, a multi-scale climate model backed by the U.S. Department of Energy. Because ML emulators are significantly cheaper to inference than MMF, progress on this front can help scie...","","https://www.kaggle.com/competitions/leap-atmospheric-physics-ai-climsim","completed","8","","2024-04-18","2024-07-15","2648","2024-12-09 18:18:19","2024-12-09 18:18:25"
"534","owkin-and-servier-ai-hackathon-for-glioblastoma-research","Owkin & Servier AI Hackathon for Glioblastoma Research","Join the hackathon to advance glioblastoma research through AI","Join the hackathon to advance glioblastoma research through the use of AI and multimodal patient data","","https://www.owkin.com/connect/glioblastoma-ai-hackathon","upcoming","\N","","2025-02-03","2025-02-04","2944","2024-12-18 18:43:47","2024-12-18 18:47:44"
"535","deep-learning-epilepsy-detection-challenge","Deep Learning Epilepsy Detection Challenge","","Develop proof-of-concept for a seizure detection system that is sensitive, automated, patient-specific, and tunable to maximise sensitivity while minimizing human annotation times using custom data preparation methods, deep learning analytics and electroencephalography (EEG) data.","","","completed","\N","10.1016/j.ebiom.2021.103275","2020","2020","794","2025-01-13 19:18:38","2025-01-13 19:33:44"
"535","deep-learning-epilepsy-detection-challenge","Deep Learning Epilepsy Detection Challenge","","Develop proof-of-concept for a seizure detection system that is sensitive, automated, patient-specific, and tunable to maximise sensitivity while minimizing human annotation times using custom data preparation methods, deep learning analytics and electroencephalography (EEG) data.","","","completed","\N","10.1016/j.ebiom.2021.103275","2020-01-01","2020-01-01","794","2025-01-13 19:18:38","2025-01-13 19:33:44"
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