{"id":17338219,"url":"https://github.com/lcwong0928/ehreader","last_synced_at":"2025-09-06T22:36:52.301Z","repository":{"id":129687945,"uuid":"484817150","full_name":"lcwong0928/ehreader","owner":"lcwong0928","description":"A question-answering system for electronic health records to ease physician workload.","archived":false,"fork":false,"pushed_at":"2022-04-23T18:06:29.000Z","size":19757,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-10T20:46:53.025Z","etag":null,"topics":["bert-models","electronic-health-record","question-answering"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/lcwong0928.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-04-23T17:45:59.000Z","updated_at":"2022-10-11T14:36:37.000Z","dependencies_parsed_at":"2023-04-19T00:35:26.358Z","dependency_job_id":null,"html_url":"https://github.com/lcwong0928/ehreader","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/lcwong0928/ehreader","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lcwong0928%2Fehreader","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lcwong0928%2Fehreader/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lcwong0928%2Fehreader/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lcwong0928%2Fehreader/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lcwong0928","download_url":"https://codeload.github.com/lcwong0928/ehreader/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lcwong0928%2Fehreader/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":273973961,"owners_count":25200578,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-09-06T02:00:13.247Z","response_time":2576,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["bert-models","electronic-health-record","question-answering"],"created_at":"2024-10-15T15:37:33.057Z","updated_at":"2025-09-06T22:36:52.280Z","avatar_url":"https://github.com/lcwong0928.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# EHReader: A Medical Healthcare Question Answering System\n\n## Introduction\n\nQuestion answering (QA) is a prominent challenge in natural language processing research that requires machines to\npredict the correct answer to a posed question by extracting it from a given context. In some cases, QA tasks also\ninvolve determining \"answerability\": whether the answer is present at all in the passage. Recent research has begun to\nexplore domain-specific QA systems, such as for usage in medical contexts. The growing adoption of electronic health\nrecords (EHR) in the healthcare system poses a specific QA challenge: retrieving answers from clinical notes to inform\nmedical decisions. This paper introduces the EHReader model based on the Retrospective Reader architecture. The EHReader\nmodel incorporates quick reading and deep reading modules, enabling it to evaluate answerability and then verify the\nanswer more comprehensively quickly. We compare EHReader to baseline DistilBERT and BioBERT models for medical QA tasks.\nThe proposed model incorporating only the QuickReader module achieves state-of-the-art results on the benchmark EmrQA\nmedical dataset and outperforms the baseline DistilBERT and BioBERT models.\n\n## Links\n\n[Report](https://github.com/lcwong0928/ehreader/blob/main/results/report.pdf) \\\n[Presentation](https://github.com/lcwong0928/ehreader/blob/main/results/presentation.pdf)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flcwong0928%2Fehreader","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flcwong0928%2Fehreader","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flcwong0928%2Fehreader/lists"}