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Artificial Intelligence Hackathon at SIO2020
The SIO announces the 1st Artificial Intelligence Hackathon to be held at the upcoming SIO meeting in New Orleans on 1 February 2020.
Motto: “From Code To Bedside”
The SIO Artificial Intelligence Hackathon is a 1 hour open session at the annual SIO meeting 2020 in New Orleans that will give selected teams the opportunity to pitch their AI-based research project proposals with high translational value to a judging panel composed of SIO research committee members and industry representatives on the criteria of healthcare impact, innovation, translatability to product, and presentation. The winning team will receive a $7000 seed grant. The invited teams will be given 5 minutes of time to pitch their project and propose an AI-based solution to a specific clinical problem in IO, followed by 1 minutes of Q/A by the judging panel. The proposal should have a high translational value and implementation should have immediate impact on cancer care in a multi-disciplinary setting.
Hackathon Pitches:
Session: Saturday, 1 February, 4:15 pm-5:45 pm, Galerie 1/2/3, 2nd Floor.
Speaker |
Topic |
Julius Chapiro, MD, PhD Yale University |
Welcome and introduce judging panel |
Ben Hsieh, MS Rhode Island Hospital |
Intra-Procedure Prediction of Tumor Recurrence |
Charlie Hamm, MD Institute of Radiology Charité |
Interpretable deep learning classification of prostate cancer on MRI |
Chenyang Zhan, MD, PhD NYU School of Medicine |
Utility of supervised machine learning techniques to predict Y90 radioembolization treatment response for HCC based on pre-procedural clinical data and imaging features |
Matthias Stechele, MD Klinik und Poliklinik für Radiologie |
Radioembolization of HCC: Data-driven prognosis and subgroup identification |
John Swietlik, MD University of Wisconsin School of Medicine and Public Health |
Machine Learning to Identify Active Extravasation on Arteriograms |
Leigh Casadaban, MD Brigham and Women's Hospital |
Feasibility Study of Deep Learning Convolutional Neural Networks to Predict Clinical Benefit of Transarterial Radioembolization Using Pretreatment CT and SPECT Imaging |
William Wagstaff, MD, MS Emory University Hospital |
Deep Learning Dosimetry: Automated Treatment Dose Calculations for Yttrium-90 Radioembolization of Hepatocellular Carcinoma |
Joe Cavallo, MD Yale New Haven Hospital Brian Letzen, MD, MS Yale New Haven Hospital |
Unboxing AI: Deep Learning Based Diagnosis of HCC using Explainable A.I. Technology |
Brett Marinelli, MD Icahn School of Medicine at Mount Sinai |
Deep Learning Deformable Co-registration for Accurate Multi-modal Navigational Guidance in Liver Interventions |
Rajesh Shah, MD VA Palo Alto Health Care System |
AI for Automated Diagnosis of Lung Cancer Subtypes |
Joe Erinjeri, MD, PhD Memorial Sloan Kettering Cancer Center |
Selecting Optimal Physicians for Consultation and Procedures using Unsupervised, Multi-Class Text Classification Deep Learning of Interventional Radiology Reports |
Judging Panel: Matt Callstrom, MD, PhD, Martijn Meijerink, MD, PhD, Luigi Solbiati, MD,
Terence Gade, MD, PhD, Isabel Newton, MD, PhD, Charles Stanley (Guerbet), MingDe Lin, PhD (Visage Imaging)
The winning team of SIO's First AI Hackathon will be announced at
SIO2020 Game Night, Saturday, 1 February, 6pm.
THE SIO THANKS GUERBET AND VISAGE IMAGING, INC. FOR
SUPPORTING AND SPONSORING THIS CALL.