{"id":28306314,"url":"https://github.com/ttsudipto/sdldpred","last_synced_at":"2026-04-09T17:50:00.149Z","repository":{"id":185578049,"uuid":"642743695","full_name":"ttsudipto/sdldpred","owner":"ttsudipto","description":"SDLDpred - Symptom-based Drugs of Lifestyle-related Diseases prediction","archived":false,"fork":false,"pushed_at":"2024-07-01T10:26:43.000Z","size":21075,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-22T04:49:38.783Z","etag":null,"topics":["birch","bisecting-kmeans","clustering","css","drug-prediction","drug-symptom-associations","html","js","kmeans","lifestyle-diseases","machine-learning","mean-shift","php","scikit-learn","semantic-similarity","symptoms","web-application"],"latest_commit_sha":null,"homepage":"http://bicresources.jcbose.ac.in/ssaha4/sdldpred/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ttsudipto.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,"zenodo":null}},"created_at":"2023-05-19T08:48:11.000Z","updated_at":"2024-12-10T02:14:22.000Z","dependencies_parsed_at":null,"dependency_job_id":"bff28b09-3f82-4a9d-8454-a5bba1b08623","html_url":"https://github.com/ttsudipto/sdldpred","commit_stats":null,"previous_names":["ttsudipto/sdldpred"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ttsudipto/sdldpred","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ttsudipto%2Fsdldpred","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ttsudipto%2Fsdldpred/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ttsudipto%2Fsdldpred/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ttsudipto%2Fsdldpred/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ttsudipto","download_url":"https://codeload.github.com/ttsudipto/sdldpred/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ttsudipto%2Fsdldpred/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28133025,"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":"2025-12-30T02:00:05.476Z","response_time":64,"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":["birch","bisecting-kmeans","clustering","css","drug-prediction","drug-symptom-associations","html","js","kmeans","lifestyle-diseases","machine-learning","mean-shift","php","scikit-learn","semantic-similarity","symptoms","web-application"],"created_at":"2025-05-24T03:36:21.894Z","updated_at":"2025-12-30T22:07:00.526Z","avatar_url":"https://github.com/ttsudipto.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# SDLDpred - Symptom-based Drugs of Lifestyle-related Diseases prediction\n\nSDLDpred is a web-based tool to predict drugs of lifestyle-related diseases using symptoms\nas features.\n\nIt uses an unsupervised machine learning model trained using Bisecting K-Means algorithm to\nperform the prediction. The model was trained with *novel drug-symptom associations* computed\nfrom the disease-symptom and drug-disease association data of *143 lifestyle-related diseases*, \n*1271 drugs* and *305 symptoms*.\n\n **Cite as:**\n\n\u003eBhattacharjee, S., Saha, B., \u0026 Saha, S. (2024). Symptom-based drug prediction of\nlifestyle-related chronic diseases using unsupervised machine learning techniques. *Computers\nin Biology and Medicine*, 174, 108413.\u003cbr/\u003e\n[https://doi.org/10.1016/j.compbiomed.2024.108413](https://doi.org/10.1016/j.compbiomed.2024.108413).\n\n## Using the tool\n\nSDLDpred is available at: [http://bicresources.jcbose.ac.in/ssaha4/sdldpred](http://bicresources.jcbose.ac.in/ssaha4/sdldpred).\n\nTo know more about the datasets and the methodology, please refer to the \n[About](http://bicresources.jcbose.ac.in/ssaha4/pulmopred/about.html) page. Please refer to \nthe [Help](http://bicresources.jcbose.ac.in/ssaha4/pulmopred/help.html) page for understanding \nthe inputs and outputs to the web application.\n\n## Development\n\nPython libraries used :\n\n* numpy (Version `1.24.1`)\n* scikit-learn (Version `1.2.1`)\n* joblib (Version `1.2.0`)\n* scipy (Version `1.10.1`)\n* ssmpy (Version `0.2.5`)\n\nR libraries used :\n\n* GOSemSim (Version `2.26.0`)\n* clusterProfiler (Version `4.8.1`)\n* fmcsR (Version `1.42.0`)\n* ggplot2 (Version `3.4.2`)\n* ggpubr (Version `0.6.0`)\n* patchwork (Version `1.1.2`)\n* pheatmap (Version `1.0.12`)\n\nThe web application is deployed in an Apache HTTP server.\n\n## Team\n* **Sudipto Bhattacharjee** *([ttsudipto@gmail.com](mailto:ttsudipto@gmail.com))*\u003cbr/\u003e\n  Ph.D. Scholar,\u003cbr/\u003e\n  Department of Computer Science and Engineering,\u003cbr/\u003e\n  University of Calcutta, Kolkata, India.\u003cbr/\u003e\n* **Dr. Banani Saha** *([bsaha_29@yahoo.com](mailto:bsaha_29@yahoo.com))*\u003cbr/\u003e\n  Associate Professor,\u003cbr/\u003e\n  Department of Computer Science and Engineering,\u003cbr/\u003e\n  University of Calcutta, Kolkata, India.\n* **Dr. Sudipto Saha** *([ssaha4@jcbose.ac.in](mailto:ssaha4@jcbose.ac.in))*\u003cbr/\u003e\n  Associate Professor,\u003cbr/\u003e\n  Department of Biological Sciences,\u003cbr/\u003e\n  Bose Institute, Kolkata, India.\n  \n*Please contact Dr. Sudipto Saha regarding any further queries.*\n\n*This tool is strictly for research use only. It should be used for medical purposes only by consulting with doctors.*\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fttsudipto%2Fsdldpred","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fttsudipto%2Fsdldpred","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fttsudipto%2Fsdldpred/lists"}