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English
$
USD
I will create and train dl model for medical image classification
Android and iOS App Developer , Ai ml engineer , Software Engineer
Over past 3 year, I've focused on building modern mobile applications using Flutter, turning ideas into clean, responsive, and user-friendly products. My portfolio includes e-commerce, invoice managem...
About this Gig
Healthcare and scientific imaging demand more rigor than a typical Fiverr "image classifier" gig a model that just reports high accuracy without proper validation isn't safe to use, and most sellers here don't understand that. I build medical/scientific image classification models using transfer learning (EfficientNet, ResNet) in PyTorch, with a real evaluation methodology: accuracy, precision, recall, F1-score, and confusion matrices not just a single accuracy number.
I've built and evaluated a four-class blood cell cancer classifier this way, achieving strong classification metrics and deploying it through a Flask/FastAPI interface for real-time predictions.
What I can help with: cell/tissue classification, disease detection from scans (X-ray, MRI, histopathology), skin lesion classification, plant/crop disease detection, or any scientific image classification task where you need a defensible, well-evaluated model not just a black box.
Important: This is a research/development tool, not a certified medical device. Results are not a substitute for professional clinical diagnosis, and I'll include a responsible-use disclaimer in every delivery.
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FAQ
Do I need to provide the dataset?
Yes — you provide labeled images (or a public dataset link). I can advise on dataset size/quality if you're unsure.
What if my dataset is small or imbalanced?
I use data augmentation and class-weighting/oversampling techniques to handle this — common in medical imaging where certain classes are rare.
How do I know the model is actually reliable?
Every delivery includes a full evaluation report: confusion matrix, precision, recall, F1-score, and (on Premium) Grad-CAM visualizations showing which image regions influenced predictions.
Is this cleared for clinical/diagnostic use?
No — this is a research and development tool. It's not a certified medical device and should not be used for clinical diagnosis without proper regulatory validation and professional oversight.
