You will get a medical imaging AI model for detection and segmentation
Project details
Custom deep learning models for medical and scientific imaging — built by an ML engineer with a proven track record across dermatology, neurology and radiology pipelines, currently pursuing a Master's in Biomedical Engineering.
RELEVANT WORK:
• Melanoma detection: skin lesion classification with interpretability heatmaps
• Brain tumor MRI: 3D auto-segmentation with attention architectures
• Chest X-ray diagnosis: multi-condition classification plus radiology-report NLP
WHAT I DELIVER:
• Honest feasibility analysis of your dataset before you commit
• Model training with rigorous evaluation (sensitivity, specificity, AUC — not just "accuracy")
• Interpretability built in, so clinicians can see WHY the model decided
• Clean, reproducible code you fully own, with deployment support
Note: I deliver research and decision-support software — regulatory certification (FDA/CE) of a medical device is a separate process I can advise on but not provide.
Message me with your imaging modality, dataset size and target task — I'll give you a straight feasibility answer within 24 hours.
RELEVANT WORK:
• Melanoma detection: skin lesion classification with interpretability heatmaps
• Brain tumor MRI: 3D auto-segmentation with attention architectures
• Chest X-ray diagnosis: multi-condition classification plus radiology-report NLP
WHAT I DELIVER:
• Honest feasibility analysis of your dataset before you commit
• Model training with rigorous evaluation (sensitivity, specificity, AUC — not just "accuracy")
• Interpretability built in, so clinicians can see WHY the model decided
• Clean, reproducible code you fully own, with deployment support
Note: I deliver research and decision-support software — regulatory certification (FDA/CE) of a medical device is a separate process I can advise on but not provide.
Message me with your imaging modality, dataset size and target task — I'll give you a straight feasibility answer within 24 hours.
Machine Learning Tools
Keras, MLflow, NumPy, OpenCV, pandas, Python, PyTorch, scikit-learn, TensorFlowWhat's included
| Service Tiers |
Starter
$495
|
Standard
$1,250
|
Advanced
$2,500
|
|---|---|---|---|
| Delivery Time | 10 days | 21 days | 35 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 1 | 2 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 3 | 6 | 10 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | - | |
Source Code |
Optional add-ons
You can add these on the next page.
Additional Revision
+$100
Additional Model Variation
(+ 5 Days)
+$350
Additional imaging task or modality
(+ 7 Days)
+$400
Report-text NLP module
(+ 6 Days)
+$350
Annotation strategy consulting
(+ 3 Days)
+$200Frequently asked questions
About Eduardo
AI/ML Engineer | LLM, RAG & AI Agents | Azure Certified | PhD
Naguanagua, Venezuela - 3:23 pm local time
With 8+ years in AI/ML and a PhD in Computer Systems, I specialize in:
🔹 LLM Applications & RAG Custom chatbots, document Q&A, and knowledge assistants using GPT, Claude, Llama, LangChain, LlamaIndex, and vector databases (Pinecone, ChromaDB). One of my RAG systems for a healthcare company achieved 95%+ clinical accuracy.
🔹 AI Agents & Automation Multi-agent systems with LangGraph, AutoGen, and Semantic Kernel that execute complex workflows with minimal human intervention.
🔹 Intelligent Document Processing OCR and data extraction pipelines with Azure Document Intelligence and OpenAI. I built an enterprise BOL/POD document-matching system processing documents at scale for US logistics.
🔹 Computer Vision Object detection, medical imaging (melanoma detection, MRI segmentation, chest X-ray diagnosis), and drone-image analysis using YOLO, OpenCV, PyTorch.
🔹 MLOps & Cloud End-to-end deployment on Azure (certified AI Engineer + Data Scientist), AWS, Kubernetes, TorchServe, ONNX.
Currently serving US enterprise clients. Microsoft Certified: Azure AI Engineer Associate & Azure Data Scientist Associate. AWS ML Engineer track completed.
I communicate clearly, deliver on schedule, and document everything. Message me with your use case and I'll respond within 24 hours.
Steps for completing your project
After purchasing the project, send requirements so Eduardo can start the project.
Delivery time starts when Eduardo receives requirements from you.
Eduardo works on your project following the steps below.
Revisions may occur after the delivery date.
Dataset assessment
I review your images, labels and class balance, and give you an honest feasibility read: what accuracy is realistic with your current data.
Preprocessing & baseline
I build the preprocessing pipeline and a transfer-learning baseline to establish a performance floor quickly.