{"id":20837769,"url":"https://github.com/astrazeneca/multimodal-python-course","last_synced_at":"2026-03-13T04:33:37.944Z","repository":{"id":239012378,"uuid":"788096048","full_name":"AstraZeneca/multimodal-python-course","owner":"AstraZeneca","description":"The purpose of the code is to facilitate a comprehensive understanding of multimodal data science applications within medical domain. The code serves to support the delivery of a cutting-edge workshop designed to introduce researchers to the rapidly evolving field of multimodal data science","archived":false,"fork":false,"pushed_at":"2025-07-28T08:18:57.000Z","size":11763,"stargazers_count":10,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-09-09T11:50:32.658Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/AstraZeneca.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,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2024-04-17T19:08:31.000Z","updated_at":"2025-08-24T16:44:20.000Z","dependencies_parsed_at":"2025-09-09T11:05:39.336Z","dependency_job_id":null,"html_url":"https://github.com/AstraZeneca/multimodal-python-course","commit_stats":null,"previous_names":["astrazeneca/multimodal-python-course"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/AstraZeneca/multimodal-python-course","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AstraZeneca%2Fmultimodal-python-course","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AstraZeneca%2Fmultimodal-python-course/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AstraZeneca%2Fmultimodal-python-course/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AstraZeneca%2Fmultimodal-python-course/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/AstraZeneca","download_url":"https://codeload.github.com/AstraZeneca/multimodal-python-course/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AstraZeneca%2Fmultimodal-python-course/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30458001,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-13T03:55:51.346Z","status":"ssl_error","status_checked_at":"2026-03-13T03:55:33.055Z","response_time":60,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":[],"created_at":"2024-11-18T01:08:32.541Z","updated_at":"2026-03-13T04:33:37.926Z","avatar_url":"https://github.com/AstraZeneca.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cimg align=\"right\" src=img/course_logo.jpg width=\"200\"\u003e\n\n\n## Navigating the Multimodal Map: Insights into Foundation Models\n\n### Venue\n\n![course-image](img/logo.jpg)\n\nOnline training course run by the NextGen Data Scientists, AstraZeneca\n\n\n### Trainers\n\nSylwia Majchrowska, Ricardo Mokhtari\n\n\n### Course structure and links\n\nDay | Title | Activity | Materials |\n:---:|:-----:|:--------:|:---------:|\n0 | Troubleshooting software installations | preparation | [Introduction and installations](notebooks/Day_0_Instalations.ipynb) |\n1 | SAM Concept Cove | Session | [Materials](Day_1_SAM_Concept_Cove/Day_1_SAM_Concept_Cove.ipynb) |\n2 | Multimodal data handling | Session | [Materials](Day_2_Data_Integration/Day_2_Data_Integration.ipynb) |\n\n\n### References\n\n1. LangSAM [Code](https://github.com/luca-medeiros/lang-segment-anything)\n2. Grounding DiNO [Code](https://github.com/IDEA-Research/GroundingDINO) [Paper](https://arxiv.org/abs/2303.05499)\n3. SAM [Code](https://github.com/facebookresearch/segment-anything) [Paper](https://arxiv.org/abs/2304.02643)\n4. [Attention illustrated blog](https://towardsdatascience.com/illustrated-self-attention-2d627e33b20a)\n5. [Attention video](https://www.youtube.com/watch?v=KmAISyVvE1Y)\n6. [Another attention video](https://www.youtube.com/watch?v=eMlx5fFNoYc)\n7. [Cross attention](https://www.youtube.com/watch?v=aw3H-wPuRcw\u0026list=WL\u0026index=37)\n8. [Visualise a transformer](https://bbycroft.net/llm)\n9. [The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification](https://arxiv.org/abs/2107.02314)\n10. [MMML Tutorial - ICML 2023](https://cmu-multicomp-lab.github.io/mmml-tutorial/icml2023/)\n11. [Multimodal data fusion – analysis](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007548/)\n12. [Fusion of Multi-Modal Data Stream for Clinical Event Prediction - Imon Banerjee, PhD](https://www.youtube.com/watch?v=3DroMVNb2vg)\n13. [Data-Efficient Multimodal Fusion on a Single GPU](https://arxiv.org/pdf/2312.10144.pdf)\n14. [Integrated multimodal artificial intelligence framework for healthcare applications](https://www.nature.com/articles/s41746-022-00689-4)\n15. [Inferring multimodal latent topics from electronic health records](https://www.nature.com/articles/s41467-020-16378-3)\n16. [Multimodal Risk Prediction with Physiological Signals, Medical Images and Clinical Notes](https://www.medrxiv.org/content/10.1101/2023.05.18.23290207v1)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fastrazeneca%2Fmultimodal-python-course","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fastrazeneca%2Fmultimodal-python-course","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fastrazeneca%2Fmultimodal-python-course/lists"}