{"payload":{"header_redesign_enabled":false,"results":[{"id":"291099660","archived":false,"color":"#3572A5","followers":3,"has_funding_file":false,"hl_name":"AIMedLab/DSW","hl_trunc_description":"Code and Datasets for the paper \"Estimating Individual Treatment Effects with Time-Varying Confounders\", published on ICDM 2020.","language":"Python","mirror":false,"owned_by_organization":true,"public":true,"repo":{"repository":{"id":291099660,"name":"DSW","owner_id":61663923,"owner_login":"AIMedLab","updated_at":"2020-09-05T14:56:51.187Z","has_issues":true}},"sponsorable":false,"topics":["deep-learning","time-varying-confounding","electronic-health-record","causal-inference","sepsis","individual-treatment-effects","deep-sequential-weighting"],"type":"Public","help_wanted_issues_count":0,"good_first_issue_issues_count":0,"starred_by_current_user":false}],"type":"repositories","page":1,"page_count":1,"elapsed_millis":58,"errors":[],"result_count":1,"facets":[],"protected_org_logins":[],"topics":null,"query_id":"","logged_in":false,"sign_up_path":"/signup?source=code_search_results","sign_in_path":"/login?return_to=https%3A%2F%2Fgithub.com%2Fsearch%3Fq%3Drepo%253AAIMedLab%252FDSW%2B%2Blanguage%253APython","metadata":null,"csrf_tokens":{"/AIMedLab/DSW/star":{"post":"iZQOLyuDepwtOlCZbqZ-FqRliWqITnDQkkaXozYwf_QK7a8PfiNALMIA8qiTvHqROnYuH8qBqf33RTwk4xen_Q"},"/AIMedLab/DSW/unstar":{"post":"7MOpai7jwA_rP19BLvyjI3oJ0eHxZbVJhYn_9e_onEvtxAcPt4NF9d240AD2BHdYDiYJAhcxAXrc2gwA-aomUQ"},"/sponsors/batch_deferred_sponsor_buttons":{"post":"kfQFnhB8Z81p328HEggoz7YBAtcJ2zquEUQb9KC4wsyMgPVQhp3nMLuV93RoC6RUij6TS9mEbl5zbe-3fm7tBw"}}},"title":"Repository search results"}