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cesargomarAI/README.md

Hi there, I'm Cesar! πŸ‘‹

πŸš€ Applied AI Engineer | MedTech Innovator | Saving Lives via Early Cancer Detection

I specialize in bridging the gap between State-of-the-Art AI and clinical practice. My mission is to build intelligent systems that empower healthcare professionals and enable the early detection of high-impact diseases, specifically Pancreatic Cancer.


πŸ”¬ Featured Portfolio (Healthcare AI Ecosystem)

The "Crown Jewel" of my Computer Vision work.

  • Goal: Automated 8-class classification of Colorectal Cancer (CRC) biopsies.
  • Tech: TensorFlow/Keras, EfficientNet-B0, Grad-CAM (XAI), OpenCV (QC).
  • Impact: 93% validation accuracy on the NCT Heidelberg dataset.

A hybrid LLM-Agent system for pancreatic cancer early alerts.

  • Goal: Detecting "Metabolic Decoupling" (HbA1c/BMI) in longitudinal data.
  • Tech: Python, LLM Agents (Qwen2.5-Coder), Hugging Face API, Pydantic.
  • Impact: Direct clinical reasoning through a safety-gated AI briefing engine.

Deep Learning for multi-label respiratory diagnosis.

  • Goal: Real-time detection of 8+ pathologies in X-Rays with high interpretability.
  • Tech: PyTorch, DenseNet121, Custom Grad-CAM Heatmaps.
  • Impact: Solves anatomical focus issues in traditional DenseNet architectures.

Classic Machine Learning applied to urinary biomarkers.

  • Goal: Early-stage PDAC differentiation using LYVE1, REG1B, and TFF1.
  • Tech: Scikit-learn (Random Forest), Feature Engineering, Plotly.
  • Impact: Accurate differentiation between pancreatitis and early-stage malignancy.

πŸ› οΈ Technical Arsenal

  • Deep Learning: PyTorch, TensorFlow, Keras, Computer Vision.
  • Generative AI: LLM Agents, Prompt Engineering, Hugging Face API.
  • Machine Learning: Scikit-learn, Feature Engineering, Longitudinal Data Analysis.
  • Full-Stack AI: Streamlit (Dashboards), Pydantic (Data Integrity), PDF Reporting.
  • DevOps/Tools: GitHub (CI/CD), Git, Secret Management.

🎯 Career Focus

  • 🌍 Goal: Looking for a 100% Remote Applied AI Engineer role (Preferred: Europe).
  • 🩺 Domain: Healthcare, MedTech, Digital Pathology, Radiology.
  • πŸ’¬ Status: Open to collaboration on projects that use AI for social good and life-saving applications.

πŸ“¬ Let's Connect

I am currently transitioning into the Applied AI Engineering & MedTech Innovation space. While I refine my professional profiles, I am open to discussing collaborations, remote opportunities in Europe, or technical challenges in Healthcare AI.

"Transforming complex clinical data into actionable medical insights."

Applied AI Engineer 3

Popular repositories Loading

  1. pdac-diagnostic-system pdac-diagnostic-system Public

    PDAC Diagnostic System: Applied ML system for early PDAC detection using urinary biomarkers (LYVE1, REG1B, TFF1). Features a Random Forest classifier, automated biochemical normalization, and PDF c…

    Jupyter Notebook

  2. cesargomarAI cesargomarAI Public

  3. ThoraxVisionAI ThoraxVisionAI Public

    Deep Learning system for Chest X-Ray multi-label diagnosis using DenseNet121. Features custom Grad-CAM implementation for clinical interpretability (Heatmaps) and calibrated thresholds to minimize …

    Python

  4. MetaScanAI-Precision-Suite MetaScanAI-Precision-Suite Public

    Deep Learning suite for Colorectal Cancer (CRC) histopathology. Classifies 8 tissue types using EfficientNet-B0 on the Kather Multiclass Dataset. Features Grad-CAM for XAI, Laplacian-based QC, and …

    Python

  5. PDAC-Sentinel-V3.0 PDAC-Sentinel-V3.0 Public

    AI-driven Clinical Support System for early PDAC detection. Identifying metabolic decoupling (HbA1c/BMI) using a hybrid approach (Deterministic Logic + LLMs) to save lives through timely intervention.

    Python