{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/automated-multi-task-learning-for-joint","title":"Automated Multi-Task Learning for Joint Disease Prediction on Electronic Health Records","arxiv_id":"2403.04086","date":"2024-03-06","proceeding":null,"authors":["Suhan Cui","Prasenjit Mitra"],"abstract":"In the realm of big data and digital healthcare, Electronic Health Records (EHR) have become a rich source of information with the potential to improve patient care and medical research. In recent years, machine learning models have proliferated for analyzing EHR data to predict patients future health conditions. Among them, some studies advocate for multi-task learning (MTL) to jointly predict multiple target diseases for improving the prediction performance over single task learning. Nevertheless, current MTL frameworks for EHR data have significant limitations due to their heavy reliance on human experts to identify task groups for joint training and design model architectures. To reduce human intervention and improve the framework design, we propose an automated approach named AutoDP, which can search for the optimal configuration of task grouping and architectures simultaneously. To tackle the vast joint search space encompassing task combinations and architectures, we employ surrogate model-based optimization, enabling us to efficiently discover the optimal solution. Experimental results on real-world EHR data demonstrate the efficacy of the proposed AutoDP framework. It achieves significant performance improvements over both hand-crafted and automated state-of-the-art methods, also maintains a feasible search cost at the same time. Source code can be found via the link: \\url{https://github.com/SH-Src/AutoDP}.","url_abs":"https://arxiv.org/abs/2403.04086v3","url_pdf":"https://arxiv.org/pdf/2403.04086v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"automated-multi-task-learning-for-joint","repo_url":"https://github.com/sh-src/autodp","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"disease-prediction","task_name":"Disease Prediction"},{"task_slug":"multi-task-learning","task_name":"Multi-Task Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2403.04086","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.04086"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"deterministic:regex_extraction","url":"https://github.com/SH-Src/AutoDP","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/sh-src/autodp","reach":{"status":"ok"}}],"summary":{"ran":3,"ran_draft_wrong":4,"unverified":3},"by_repo_kind":{"official":{"samples":10,"ran":7,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":10,"samples":[{"code_sha256_prefix":"d02832ede07c6c61","entry":"DAG","repo":"sh-src/autodp","repo_kind":"official","path":"model/surrogate.py","file_url":"https://github.com/sh-src/autodp/blob/HEAD/model/surrogate.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"d02832ede07c6c61"}},{"code_sha256_prefix":"cd44d9862276aecb","entry":"eval_metric","repo":"sh-src/autodp","repo_kind":"official","path":"utils/experiments.py","file_url":"https://github.com/sh-src/autodp/blob/HEAD/utils/experiments.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"cd44d9862276aecb"}},{"code_sha256_prefix":"03fb0d30acd33ec6","entry":"forward_sur","repo":"sh-src/autodp","repo_kind":"official","path":"active_search.py","file_url":"https://github.com/sh-src/autodp/blob/HEAD/active_search.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"03fb0d30acd33ec6"}},{"code_sha256_prefix":"f27a64c561f16250","entry":"get_data_loader1","repo":"SH-Src/AutoDP","repo_kind":"official","path":"utils/ehr_dataset.py","file_url":"https://github.com/SH-Src/AutoDP/blob/HEAD/utils/ehr_dataset.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"f27a64c561f16250"}},{"code_sha256_prefix":"0a7facc355b59543","entry":"get_datasets","repo":"SH-Src/AutoDP","repo_kind":"official","path":"utils/ehr_dataset.py","file_url":"https://github.com/SH-Src/AutoDP/blob/HEAD/utils/ehr_dataset.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"0a7facc355b59543"}},{"code_sha256_prefix":"a9a9934506c49a8e","entry":"meta_collate","repo":"sh-src/autodp","repo_kind":"official","path":"model/surrogate.py","file_url":"https://github.com/sh-src/autodp/blob/HEAD/model/surrogate.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"a9a9934506c49a8e"}},{"code_sha256_prefix":"d3688c1959313c1b","entry":"read_timeseries","repo":"sh-src/autodp","repo_kind":"official","path":"utils/experiments.py","file_url":"https://github.com/sh-src/autodp/blob/HEAD/utils/experiments.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"d3688c1959313c1b"}},{"code_sha256_prefix":"2810a41c73ecd2fe","entry":"Surrogate","repo":"sh-src/autodp","repo_kind":"official","path":"model/surrogate.py","file_url":"https://github.com/sh-src/autodp/blob/HEAD/model/surrogate.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"2810a41c73ecd2fe"}},{"code_sha256_prefix":"ce266ecd2c99da86","entry":"evaluate","repo":"sh-src/autodp","repo_kind":"official","path":"utils/experiments.py","file_url":"https://github.com/sh-src/autodp/blob/HEAD/utils/experiments.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"ce266ecd2c99da86"}},{"code_sha256_prefix":"c75d22abbf2ad955","entry":"get_data_loader","repo":"SH-Src/AutoDP","repo_kind":"official","path":"utils/ehr_dataset.py","file_url":"https://github.com/SH-Src/AutoDP/blob/HEAD/utils/ehr_dataset.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"c75d22abbf2ad955"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}