Breckenridge. This week, our team attended the first conference for Artificial Intelligence in Epilepsy in Breckenridge, Colorado. I was honored to be one of the two speakers representing the epilepsy genetics field, trying to build the bridge between the impressive amount of research in machine learning and EEG analysis with our current progress and research efforts in the genetic epilepsies. In this blog post, I would like to summarize some of my impressions from this meeting and discuss two aspects where rare disease research and machine learning already intersect, namely seizure forecasting and virtual clinical trials.
Tag Archives: machine learning
Will the relevant SNPs please stand up
The flood of variants. Every re-sequencing of a genome leads to many more variants than can be validated with functional assays. Many strategies exist to select the candidate variants. Filtering on criteria might remove all variants so efforts are focused to re-rank the list of variants such that the most promising appear on top. A recent review in Nature Reviews Genetics wants to give users a hand with using the bioinformatics tools available. As a bioinformatician, I find a number of important points missing.
