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Create a Healthcare Recommendation System Using Python & Flask(Real Time Use)
Healthcare Recommendation System Build a smart health assistant web app with real-time recommendations tailored to user profiles and symptom
🏥💡 Healthcare Recommendation System – Python Project 🐍🧠
Build an intelligent system that suggests healthcare tips, services, or treatment based on user input! A practical and impactful data science project.
🔍 Key Features:
🧾 User-based health recommendations
🧠 Machine Learning + Python logic
📊 Easy to customize and expand
💬 Improves user awareness & health decision-making
🆓 Fully open source & beginner-friendly
🔗 Download & Source Code:
👉 Healthcare Recommendation Project
🌟 Get more smart projects with source code:
🔗 https://t.me/Projectwithsourcecodes
🚀 Make smarter, healthier choices — powered by AI.
#HealthcareAI #PythonProject #RecommendationSystem #DataScience #MachineLearning #StudentProject #AIForGood #OpenSourceCode #Projectwithsourcecodes
Build an intelligent system that suggests healthcare tips, services, or treatment based on user input! A practical and impactful data science project.
🔍 Key Features:
🧾 User-based health recommendations
🧠 Machine Learning + Python logic
📊 Easy to customize and expand
💬 Improves user awareness & health decision-making
🆓 Fully open source & beginner-friendly
🔗 Download & Source Code:
👉 Healthcare Recommendation Project
🌟 Get more smart projects with source code:
🔗 https://t.me/Projectwithsourcecodes
🚀 Make smarter, healthier choices — powered by AI.
#HealthcareAI #PythonProject #RecommendationSystem #DataScience #MachineLearning #StudentProject #AIForGood #OpenSourceCode #Projectwithsourcecodes
🤝 Oral Cancer Detection – Python / Deep Learning
A deep-learning project that analyses oral cavity images to detect and localise potential cancerous lesions using CNN architectures. It helps automate early screening by classifying images (benign vs malignant) and providing segmentation/localisation to assist clinicians and researchers.
Key Features
• Image preprocessing: ROI extraction, augmentation, normalization
• CNN classification (e.g., ResNet / EfficientNet) for malignancy prediction
• Segmentation module (U-Net style) to highlight affected regions
• Model evaluation with accuracy, precision, recall & confusion matrix
• Optional web interface for image upload and instant prediction
🔗 Explore the full project here:
Oral Cancer Detection – View Project
📢 Discover more projects:
https://t.me/Projectwithsourcecodes
#Python #DeepLearning #ComputerVision #OralCancer #HealthcareAI #MedicalImaging #CNN #UNet #MLProject #DataScience #AIForGood #ProjectShowcase
A deep-learning project that analyses oral cavity images to detect and localise potential cancerous lesions using CNN architectures. It helps automate early screening by classifying images (benign vs malignant) and providing segmentation/localisation to assist clinicians and researchers.
Key Features
• Image preprocessing: ROI extraction, augmentation, normalization
• CNN classification (e.g., ResNet / EfficientNet) for malignancy prediction
• Segmentation module (U-Net style) to highlight affected regions
• Model evaluation with accuracy, precision, recall & confusion matrix
• Optional web interface for image upload and instant prediction
🔗 Explore the full project here:
Oral Cancer Detection – View Project
📢 Discover more projects:
https://t.me/Projectwithsourcecodes
#Python #DeepLearning #ComputerVision #OralCancer #HealthcareAI #MedicalImaging #CNN #UNet #MLProject #DataScience #AIForGood #ProjectShowcase