{"url":"/task/disease-trajectory-forecasting","name":"Disease Trajectory Forecasting","slug":"disease-trajectory-forecasting","description_markdown":null,"categories":[{"name":"Computer Vision","url":"/area/computer-vision"},{"name":"Medical","url":"/area/medical"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"derived"},"counts":{"papers_tagged":6,"papers_with_code":4,"benchmarks":1,"benchmark_tables_in_archive":1,"benchmark_tables_shown":1,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":0,"subtasks":0,"parent_tasks":1},"benchmarks":[{"leaderboard":"/sota/disease-trajectory-forecasting-on-uk-cf-trust","slug":"disease-trajectory-forecasting-on-uk-cf-trust","dataset":"UK CF trust","dataset_url":null,"rows_in_archive":3,"metrics":["AUC (ABPA)","AUC (Diabetes)","AUC (I. Obstruction)","I. Obstruction","AUC (K. Pneumonia)","AUC (E. Coli)","AUC (Aspergillus)"],"first_row_in_archive_order":{"model":"PASS","paper_title":"Forecasting Individualized Disease Trajectories using Interpretable Deep Learning","paper_url":"/paper/forecasting-individualized-disease","paper_date":"2018-10-24","arxiv_id":"1810.10489","code_links":[],"syntology":null}}],"datasets":[],"subtasks":[],"parent_tasks":[{"url":"/task/disease-prediction","name":"Disease Prediction"}],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":4,"of":4,"tagged_in_all":6,"items":[{"url":"/paper/deepprog-a-transformer-based-framework-for","title":"CLIMAT: Clinically-Inspired Multi-Agent Transformers for Knee Osteoarthritis Trajectory Forecasting","date":"2021-04-08","arxiv_id":"2104.03642","repositories_listed":2,"syntology":null},{"url":"/paper/clinically-inspired-multi-agent-transformers","title":"Clinically-Inspired Multi-Agent Transformers for Disease Trajectory Forecasting from Multimodal Data","date":"2022-10-25","arxiv_id":"2210.13889","repositories_listed":1,"syntology":null},{"url":"/paper/learning-dynamic-and-personalized-comorbidity","title":"Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes","date":"2020-01-08","arxiv_id":"2001.02585","repositories_listed":1,"syntology":null},{"url":"/paper/retain-an-interpretable-predictive-model-for","title":"RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism","date":"2016-08-19","arxiv_id":"1608.05745","repositories_listed":1,"syntology":null}],"syntology_records":0,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}