MedHack19-01: Health data machine learning Hackathon at UTHealth |
Website | https://sbmi.uth.edu/hackathon/ |
Submission link | https://easychair.org/conferences/?conf=medhack1901 |
We are organizing a Machine Learning Hackathon at the UTHealth School of Biomedical Informatics, September 14 – 15, 2019. The theme of this hackathon is to detect the onset of slow activity after seizures with time series EEG input data (measured from 13 electrodes). The duration between the start of the seizure and the end of postictal generalized EEG suppression (PGES) characterized by the onset of slow activity is believed to be an important risk factor to Sudden Unexpected Death in Epilepsy (SUDEP). This coding Hackathon will be a fun challenge for all students, followed by awards to the winners and demonstrations. We will invite our leader board competitents to submit paper together with us.
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
- Full papers We will follow the BMC style guideline (https://bmcmedinformdecismak.biomedcentral.com/submission-guidelines) and each paper is limited to 8 pages excluding references
Committees
Program Committee
- Dr. Samden Lhatoo
- Dr. Guo-Qiang Zhang
- Dr. Shayan Shams
- Dr. Licong Cui
- Dr. Shiqiang Tao
- Dr. Xiaojin Li
Organizing committee
- Dr. Xiaoqian Jiang
- Dr. Yejin Kim
Contact
All questions about submissions should be emailed to xiaoqian.jiang@uth.tmc.edu or yejin.kim@uth.tmc.edu