{"id":40,"date":"2023-07-04T14:56:59","date_gmt":"2023-07-04T14:56:59","guid":{"rendered":"https:\/\/eslweb.epfl.ch\/epilepsybenchmarks\/?page_id=40"},"modified":"2023-09-22T16:21:10","modified_gmt":"2023-09-22T16:21:10","slug":"tools","status":"publish","type":"page","link":"https:\/\/eslweb.epfl.ch\/epilepsybenchmarks\/tools\/","title":{"rendered":"Tools"},"content":{"rendered":"\n<p>We provide certain tools to encourage reproducibility and consistency of results reported in the field of automated seizure detection algorithm<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Library for measuring performance of seizure detection algorithms<\/h2>\n\n\n\n<p>We built a library that provides different scoring methodologies to compare a reference time series with binary annotation (ground-truth annotations of the neurologist) to hypothesis binary annotations (provided by a machine learning pipeline). These different scoring methodologies provide a count of correctly identified events (True Positives) as well as missed events (False Negatives) and wrongly marked events (False positions)<\/p>\n\n\n\n<p>In more details, we measures performance on the level of:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Samples : Performance metric that threats every label sample independently.<br><\/li>\n\n\n\n<li>Events (e.g. epileptic seizure) : Classifies each event in both reference and hypothesis based on overlap of both.<\/li>\n<\/ul>\n\n\n\n<p>Both methods are illustrated in the following figures :<\/p>\n\n\n\n<figure class=\"wp-block-image\"><a href=\"https:\/\/user-images.githubusercontent.com\/747240\/248309097-b7f76fde-c87a-41df-812d-9821375b640e.png\" target=\"_blank\" rel=\"noreferrer noopener\"><img decoding=\"async\" src=\"https:\/\/user-images.githubusercontent.com\/747240\/248309097-b7f76fde-c87a-41df-812d-9821375b640e.png\" alt=\"Illustration of sample based scoring.\"\/><\/a><\/figure>\n\n\n\n<figure class=\"wp-block-image\"><a href=\"https:\/\/user-images.githubusercontent.com\/747240\/248308898-64b4ae39-d02f-4f06-9b10-f07aaf6110d1.png\" target=\"_blank\" rel=\"noreferrer noopener\"><img decoding=\"async\" src=\"https:\/\/user-images.githubusercontent.com\/747240\/248308898-64b4ae39-d02f-4f06-9b10-f07aaf6110d1.png\" alt=\"Illustration of event based scoring.\"\/><\/a><\/figure>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-right is-layout-flex wp-container-core-buttons-is-layout-d445cf74 wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/github.com\/esl-epfl\/epilepsy_performance_metrics\"> <i class=\"fa-brands fa-github\" style=\"color: #ffffff;\"><\/i> Github repo<\/a><\/div>\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><a href=\"https:\/\/github.com\/esl-epfl\/sz-validation-framework#seizure-validation-framework\">Seizure validation Framework<\/a><\/h2>\n\n\n\n<p>This library provides script to work with the framework for the validation of EEG based automated seizure detection algorithms.<\/p>\n\n\n\n<p>The library provides code to :<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Convert EDF files from most open scalp EEG datasets of people with epilepsy to a standardized format<\/li>\n\n\n\n<li>Convert seizure annotations from these datasets to a standardized format.<\/li>\n\n\n\n<li>Evaluate the performance of seizure detection algorithm.<\/li>\n<\/ol>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-right is-layout-flex wp-container-core-buttons-is-layout-d445cf74 wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/github.com\/esl-epfl\/sz-validation-framework#seizure-validation-framework\"> <i class=\"fa-brands fa-github\" style=\"color: #ffffff;\"><\/i> Github repo<\/a><\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>We provide certain tools to encourage reproducibility and consistency of results reported in the field of automated seizure detection algorithm Library for measuring performance of seizure detection algorithms We built a library that provides different scoring methodologies to compare a reference time series with binary annotation (ground-truth annotations of the neurologist) to hypothesis binary annotations [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"inline_featured_image":false,"footnotes":""},"class_list":["post-40","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/eslweb.epfl.ch\/epilepsybenchmarks\/wp-json\/wp\/v2\/pages\/40","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/eslweb.epfl.ch\/epilepsybenchmarks\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/eslweb.epfl.ch\/epilepsybenchmarks\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/eslweb.epfl.ch\/epilepsybenchmarks\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/eslweb.epfl.ch\/epilepsybenchmarks\/wp-json\/wp\/v2\/comments?post=40"}],"version-history":[{"count":4,"href":"https:\/\/eslweb.epfl.ch\/epilepsybenchmarks\/wp-json\/wp\/v2\/pages\/40\/revisions"}],"predecessor-version":[{"id":206,"href":"https:\/\/eslweb.epfl.ch\/epilepsybenchmarks\/wp-json\/wp\/v2\/pages\/40\/revisions\/206"}],"wp:attachment":[{"href":"https:\/\/eslweb.epfl.ch\/epilepsybenchmarks\/wp-json\/wp\/v2\/media?parent=40"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}