{"id":29061660,"url":"https://github.com/tejaswinisgit/diagnosis","last_synced_at":"2026-04-17T03:01:09.566Z","repository":{"id":301322557,"uuid":"1008861193","full_name":"TejaswinisGit/Diagnosis","owner":"TejaswinisGit","description":"Real-time Identification of Pneumonia from X-ray Images using Deep Learning","archived":false,"fork":false,"pushed_at":"2025-06-26T08:53:23.000Z","size":7,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"master","last_synced_at":"2025-06-26T09:38:06.840Z","etag":null,"topics":["cnn","codeclause-internship","deep-learning","healthcare-ai","keras","medical-image-analysis","pneumonia","tensorflow","xray"],"latest_commit_sha":null,"homepage":"https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/TejaswinisGit.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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":"2025-06-26T07:52:02.000Z","updated_at":"2025-06-26T09:01:52.000Z","dependencies_parsed_at":"2025-06-26T09:38:09.051Z","dependency_job_id":"7252decd-ff34-4303-946c-b01c45f5efc4","html_url":"https://github.com/TejaswinisGit/Diagnosis","commit_stats":null,"previous_names":["tejaswinisgit/diagnosis"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/TejaswinisGit/Diagnosis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TejaswinisGit%2FDiagnosis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TejaswinisGit%2FDiagnosis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TejaswinisGit%2FDiagnosis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TejaswinisGit%2FDiagnosis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/TejaswinisGit","download_url":"https://codeload.github.com/TejaswinisGit/Diagnosis/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TejaswinisGit%2FDiagnosis/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":262219803,"owners_count":23276888,"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":["cnn","codeclause-internship","deep-learning","healthcare-ai","keras","medical-image-analysis","pneumonia","tensorflow","xray"],"created_at":"2025-06-27T08:03:14.526Z","updated_at":"2026-04-17T03:01:04.509Z","avatar_url":"https://github.com/TejaswinisGit.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🩺 Pneumonia Diagnosis from Chest X-rays using CNN\n\nThis project uses **Convolutional Neural Networks (CNNs)** to classify chest X-ray images as either **Pneumonia** or **Normal**. It was developed as part of my internship to explore deep learning in medical image analysis.\n\nBy training the model on labeled chest X-ray data, it can automatically learn the visual patterns associated with pneumonia, helping in faster and automated preliminary diagnosis.\n\n---\n\n## 📌 Highlights\n\n- 📂 Dataset: Chest X-ray images (2 classes: Pneumonia, Normal)\n- 🧠 Model: CNN built using TensorFlow and Keras\n- 🖼️ Input: Grayscale images resized to (150x150)\n- ⚙️ Training \u0026 Validation: Using Keras ImageDataGenerator\n- 📈 Output: Accuracy and loss graphs\n\n---\n\n## 🚀 How to Run the Project\n\n### 1. Clone the repository:\n```bash\ngit clone https://github.com/TejaswinisGit/Diagnosis.git\ncd Diagnosis\n```\n\n### 2. Install required libraries:\n```bash\npip install tensorflow matplotlib numpy\n```\n\n### 3. Prepare dataset:\n- Place your X-ray images in a `chest_xray` folder with this structure:\n  ```\n  chest_xray/\n  ├── train/\n  │   ├── NORMAL/\n  │   └── PNEUMONIA/\n  ├── val/\n  │   ├── NORMAL/\n  │   └── PNEUMONIA/\n  └── test/\n      ├── NORMAL/\n      └── PNEUMONIA/\n  ```\n\n### 4. Run the script:\n```bash\npython Diagnosis.py\n```\n\n---\n\n## 📚 What I Learned\n\nThrough this project, I gained practical experience in:\n\n- Preprocessing real-world medical image data\n- Using CNNs to detect visual patterns\n- Understanding data augmentation and model overfitting\n- Applying deep learning for binary classification problems\n\nThis project helped me understand how deep learning models can be applied to the healthcare domain for faster diagnostics.\n\n---\n\n## 👩‍💻 About Me\n\nI'm **Tejaswini Thungathoorthi**, a Computer Science and Engineering student specializing in **AI and Machine Learning**. I'm passionate about using technology to solve real-world problems, and this project is a step toward impactful healthcare solutions using AI.\n\n---\n\n## 📬 Contact\n\n- 📧 Email: [tejaswini17109@gmail.com]  \n- 💼 LinkedIn: [https://www.linkedin.com/in/tejaswini-thungathoorthi-9076b2295/]\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftejaswinisgit%2Fdiagnosis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftejaswinisgit%2Fdiagnosis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftejaswinisgit%2Fdiagnosis/lists"}