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$
USD
I will build a deep learning model for medical image classification and diagnosis
Machine Learning, Deep Learning, GenAI, Computer Vision,
I am a Data Scientist specializing in Python, Scikit-learn, Pandas, NumPy, and Streamlit. I build predictive models, regression and classification systems, and time-series forecasting solutions using ...
About this Gig
Are you looking for accurate and reliable medical image classification using deep learning?
I will build a custom deep learning model to analyze and classify medical images such as X-rays, MRIs, and skin lesion scans helping researchers, clinicians, and health-tech startups make faster, data-driven decisions.
What I offer:
Image classification using CNN (ResNet, VGG, EfficientNet)
Binary & multi-class disease detection
Transfer learning for high accuracy on small datasets
Confusion matrix, accuracy & loss reports
Clean, well-commented Python code
Model export (H5 / SavedModel format)
Tools & Frameworks:
TensorFlow, Keras, OpenCV, NumPy, Matplotlib
Why choose me?
I specialize in medical imaging projects with real hands-on experience. I deliver production-ready models with full documentation so you understand exactly what was built.
Message me before ordering to discuss your dataset and requirements.
Let's build something that makes a real impact in healthcare.
My Portfolio
FAQ
Q1: What type of medical images can you work with?
I can work with X-rays, MRI scans, CT scans, skin lesion images, histopathology slides, and retinal images. As long as your data is in standard image formats (JPG, PNG, DICOM), I can build a model around it.
Q2: What if I don't have a large dataset?
No problem. I use transfer learning techniques with pre-trained models like ResNet and EfficientNet, which are specifically designed to deliver high accuracy even on small datasets.
Q3: What will I receive as a final deliverable?
You will receive the trained model file (H5 or SavedModel), full Python source code, a performance report including accuracy, loss curves, and confusion matrix, and a README file explaining how to use the model.
Q4: Do I need to prepare my dataset before ordering?
Ideally yes — images should be organized into labeled folders. However if you need help with dataset preparation or annotation, message me first and I can include it as an add-on.
