{"id":15677120,"url":"https://github.com/sayakpaul/malaria-detection-with-deep-learning","last_synced_at":"2025-05-07T00:43:51.400Z","repository":{"id":106648993,"uuid":"184411553","full_name":"sayakpaul/Malaria-Detection-with-Deep-Learning","owner":"sayakpaul","description":"Deep learning based solution to automatically analyze medical images for malaria testing","archived":false,"fork":false,"pushed_at":"2019-05-01T13:14:47.000Z","size":40141,"stargazers_count":14,"open_issues_count":0,"forks_count":8,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-03-31T04:41:07.953Z","etag":null,"topics":["computer-vision","deep-learning","fastai","medical-imaging","resnet-34"],"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/sayakpaul.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":"2019-05-01T12:16:29.000Z","updated_at":"2024-11-06T09:54:10.000Z","dependencies_parsed_at":"2023-07-12T16:00:10.814Z","dependency_job_id":null,"html_url":"https://github.com/sayakpaul/Malaria-Detection-with-Deep-Learning","commit_stats":{"total_commits":5,"total_committers":1,"mean_commits":5.0,"dds":0.0,"last_synced_commit":"c60997afbe4671f66168272a3b44ae0a603afa82"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sayakpaul%2FMalaria-Detection-with-Deep-Learning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sayakpaul%2FMalaria-Detection-with-Deep-Learning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sayakpaul%2FMalaria-Detection-with-Deep-Learning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sayakpaul%2FMalaria-Detection-with-Deep-Learning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sayakpaul","download_url":"https://codeload.github.com/sayakpaul/Malaria-Detection-with-Deep-Learning/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252793561,"owners_count":21805053,"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","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":["computer-vision","deep-learning","fastai","medical-imaging","resnet-34"],"created_at":"2024-10-03T16:08:35.142Z","updated_at":"2025-05-07T00:43:51.291Z","avatar_url":"https://github.com/sayakpaul.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Malaria-Detection-with-Deep-Learning\n\nThe motivation of this notebook comes from a PyImageSearch tutorial [Deep Learning and Medical Image Analysis with Keras](https://www.pyimagesearch.com/2018/12/03/deep-learning-and-medical-image-analysis-with-keras/). In that tutorial, [Adrian Rosebrock ](https://www.pyimagesearch.com/author/adrian/) of PyImageSearch briefed about medical tests condicted for testing malaria and how he was able to achieve SOTA score over the work as discussed in [Pre-trained convolutional neural networks as feature extractors toward improved parasite detection in thin blood smear images](https://lhncbc.nlm.nih.gov/system/files/pub9752.pdf) by Rajaraman et al. Adrian's model was able to yield an accuracy score of **97%** with a training time of about **54 minutes** on Titan X GPU, whereas the model discussed in the paper took **almost a day** to train and generated an accuracy score of **95.9%**. \n\nSo, I decided to challenge **myself** to see if I could apply the modern deep learning practices (as taught by [Jeremy Howard](https://www.linkedin.com/in/howardjeremy) in the course[ Practical Deep Learning for Coders v3](https://course.fast.ai)) with the help of the `fastai` library. The good news is *I did*. \n\n**Note**: Be sure to check out the PyImageSearch tutorial if you interested in a more in-depth analysis of the problem.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsayakpaul%2Fmalaria-detection-with-deep-learning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsayakpaul%2Fmalaria-detection-with-deep-learning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsayakpaul%2Fmalaria-detection-with-deep-learning/lists"}