Off the back of the Melbourne University AES/MathWorks/NIH Seizure Prediction Challenge we are now launching Epilepsyecosystem.org in advance of a future Kaggle contest on seizure prediction planned for two years from now. Epilepsyecosystem.org is an online crowd-sourcing ecosystem for the long-term sharing of data and algorithms to improve the performance of seizure prediction algorithms and make seizure prediction a reality for people suffering from epilepsy.
\n\nAround twenty million people worldwide suffer from drug-resistant epilepsy and the unpredictability of seizures is one of the major factors affecting the quality of life of people with epilepsy. Accurate seizure prediction algorithms can provide warnings to encourage a patient to move to safety, or activate interventions such as electrical stimulation or drug delivery to avert seizures.
\n\nPeople with epilepsy need your love, and your algorithms, to help improve their day to day lives. To find out more visit https://www.epilepsyecosystem.org.
\n\nFurther references: Kuhlmann, L., Karoly, P., Freestone, D.R., Brinkmann, B.H., Temko, A., Barachant, A., Li, F., Titericz Jr., G., Lang, B.W., Lavery, D., Roman, K., Broadhead, D., Dobson, S., Jones, G., Tang, Q., Ivanenko, I., Panichev, O., Proix, T., Náhlík, M., Grunberg, D.B., Reuben, C., Worrell, G., Litt, B., Liley, D.T.J., Grayden, D.B., & Cook, M.J. (2018) Epilepsyecosystem.org Crowd-Sourcing Reproducible Seizure Prediction with Long-Term Human Intracranial EEG, Brain, awy210, https://doi.org/10.1093/brain/awy210 Available at: https://academic.oup.com/brain/article-lookup/doi/10.1093/brain/awy210
\n\nKuhlmann, L., Lehnertz, K., Richardson, M., Schelter, B., & Zaveri, H. (2018) Seizure prediction - ready for a new era. Nature Reviews Neurology. In Press.
\n\nLevin Kuhlmann, PhD Centre for Human Psychopharmacology Swinburne University of Technology & Departments of Medicine and Biomedical Engineering The University of Melbourne. lkuhlmann@swin.edu.au levink@unimelb.edu.au Ph: +61412 552283
", "messages": [ { "id": 369453, "postDate": "2018-08-13T04:44:44.563Z", "content": "Off the back of the Melbourne University AES/MathWorks/NIH Seizure Prediction Challenge we are now launching Epilepsyecosystem.org in advance of a future Kaggle contest on seizure prediction planned for two years from now. Epilepsyecosystem.org is an online crowd-sourcing ecosystem for the long-term sharing of data and algorithms to improve the performance of seizure prediction algorithms and make seizure prediction a reality for people suffering from epilepsy.
\n\nAround twenty million people worldwide suffer from drug-resistant epilepsy and the unpredictability of seizures is one of the major factors affecting the quality of life of people with epilepsy. Accurate seizure prediction algorithms can provide warnings to encourage a patient to move to safety, or activate interventions such as electrical stimulation or drug delivery to avert seizures.
\n\nPeople with epilepsy need your love, and your algorithms, to help improve their day to day lives. To find out more visit https://www.epilepsyecosystem.org.
\n\nFurther references: Kuhlmann, L., Karoly, P., Freestone, D.R., Brinkmann, B.H., Temko, A., Barachant, A., Li, F., Titericz Jr., G., Lang, B.W., Lavery, D., Roman, K., Broadhead, D., Dobson, S., Jones, G., Tang, Q., Ivanenko, I., Panichev, O., Proix, T., Náhlík, M., Grunberg, D.B., Reuben, C., Worrell, G., Litt, B., Liley, D.T.J., Grayden, D.B., & Cook, M.J. (2018) Epilepsyecosystem.org Crowd-Sourcing Reproducible Seizure Prediction with Long-Term Human Intracranial EEG, Brain, awy210, https://doi.org/10.1093/brain/awy210 Available at: https://academic.oup.com/brain/article-lookup/doi/10.1093/brain/awy210
\n\nKuhlmann, L., Lehnertz, K., Richardson, M., Schelter, B., & Zaveri, H. (2018) Seizure prediction - ready for a new era. Nature Reviews Neurology. In Press.
\n\nLevin Kuhlmann, PhD Centre for Human Psychopharmacology Swinburne University of Technology & Departments of Medicine and Biomedical Engineering The University of Melbourne. lkuhlmann@swin.edu.au levink@unimelb.edu.au Ph: +61412 552283
", "rawMarkdown": "Off the back of the Melbourne University AES/MathWorks/NIH Seizure Prediction Challenge we are now launching Epilepsyecosystem.org in advance of a future Kaggle contest on seizure prediction planned for two years from now. Epilepsyecosystem.org is an online crowd-sourcing ecosystem for the long-term sharing of data and algorithms to improve the performance of seizure prediction algorithms and make seizure prediction a reality for people suffering from epilepsy.\n\nAround twenty million people worldwide suffer from drug-resistant epilepsy and the unpredictability of seizures is one of the major factors affecting the quality of life of people with epilepsy. Accurate seizure prediction algorithms can provide warnings to encourage a patient to move to safety, or activate interventions such as electrical stimulation or drug delivery to avert seizures.\n\nPeople with epilepsy need your love, and your algorithms, to help improve their day to day lives. To find out more visit https://www.epilepsyecosystem.org.\n\nFurther references: Kuhlmann, L., Karoly, P., Freestone, D.R., Brinkmann, B.H., Temko, A., Barachant, A., Li, F., Titericz Jr., G., Lang, B.W., Lavery, D., Roman, K., Broadhead, D., Dobson, S., Jones, G., Tang, Q., Ivanenko, I., Panichev, O., Proix, T., Náhlík, M., Grunberg, D.B., Reuben, C., Worrell, G., Litt, B., Liley, D.T.J., Grayden, D.B., & Cook, M.J. (2018) Epilepsyecosystem.org Crowd-Sourcing Reproducible Seizure Prediction with Long-Term Human Intracranial EEG, Brain, awy210, https://doi.org/10.1093/brain/awy210 Available at: https://academic.oup.com/brain/article-lookup/doi/10.1093/brain/awy210\n\nKuhlmann, L., Lehnertz, K., Richardson, M., Schelter, B., & Zaveri, H. (2018) Seizure prediction - ready for a new era. Nature Reviews Neurology. In Press.\n\nLevin Kuhlmann, PhD Centre for Human Psychopharmacology Swinburne University of Technology & Departments of Medicine and Biomedical Engineering The University of Melbourne. lkuhlmann@swin.edu.au levink@unimelb.edu.au Ph: +61412 552283", "votes": 1 } ], "comments": [], "raw_markdown_by_id": { "369453": "Off the back of the Melbourne University AES/MathWorks/NIH Seizure Prediction Challenge we are now launching Epilepsyecosystem.org in advance of a future Kaggle contest on seizure prediction planned for two years from now. Epilepsyecosystem.org is an online crowd-sourcing ecosystem for the long-term sharing of data and algorithms to improve the performance of seizure prediction algorithms and make seizure prediction a reality for people suffering from epilepsy.\n\nAround twenty million people worldwide suffer from drug-resistant epilepsy and the unpredictability of seizures is one of the major factors affecting the quality of life of people with epilepsy. Accurate seizure prediction algorithms can provide warnings to encourage a patient to move to safety, or activate interventions such as electrical stimulation or drug delivery to avert seizures.\n\nPeople with epilepsy need your love, and your algorithms, to help improve their day to day lives. To find out more visit https://www.epilepsyecosystem.org.\n\nFurther references: Kuhlmann, L., Karoly, P., Freestone, D.R., Brinkmann, B.H., Temko, A., Barachant, A., Li, F., Titericz Jr., G., Lang, B.W., Lavery, D., Roman, K., Broadhead, D., Dobson, S., Jones, G., Tang, Q., Ivanenko, I., Panichev, O., Proix, T., Náhlík, M., Grunberg, D.B., Reuben, C., Worrell, G., Litt, B., Liley, D.T.J., Grayden, D.B., & Cook, M.J. (2018) Epilepsyecosystem.org Crowd-Sourcing Reproducible Seizure Prediction with Long-Term Human Intracranial EEG, Brain, awy210, https://doi.org/10.1093/brain/awy210 Available at: https://academic.oup.com/brain/article-lookup/doi/10.1093/brain/awy210\n\nKuhlmann, L., Lehnertz, K., Richardson, M., Schelter, B., & Zaveri, H. (2018) Seizure prediction - ready for a new era. Nature Reviews Neurology. In Press.\n\nLevin Kuhlmann, PhD Centre for Human Psychopharmacology Swinburne University of Technology & Departments of Medicine and Biomedical Engineering The University of Melbourne. lkuhlmann@swin.edu.au levink@unimelb.edu.au Ph: +61412 552283" } }