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mittal-kumar/README.md
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Education

Institution Credential Year
🌲 Stanford University Data Science in Medicine 2025
🦅 SUNY Stony Brook M.S. Biomedical Informatics 2024–25
🏛️ Sapienza University, Rome B.S. Bioinformatics 2020–23
🇪🇸 San Jorge University, Spain Erasmus Exchange 2023

⚡ I operate at the intersection of genomics and GPU clusters, turning raw EHR signals into early clinical warnings.
My work spans FHIR pipelines, HIPAA-grade governance, and deep learning systems validated on real patient outcomes across 3 continents.


📡   CLINICAL IMPACT METRICS

┌─────────────────────────────────────────────────────────────────────────────┐
│  OUTCOME DASHBOARD  ·  Real Metrics  ·  Real Patients  ·  Real Stakes       │
├──────────────────────────────┬────────────────────┬─────────────────────────┤
│  PROJECT                     │  METRIC            │  CLINICAL VALUE         │
├──────────────────────────────┼────────────────────┼─────────────────────────┤
│  ECG Fall Risk Detection     │  70.99% Accuracy   │  Elderly inpatient      │
│  (XAI / SHAP Interpretable)  │  ████████████░░░░  │  safety & intervention  │
├──────────────────────────────┼────────────────────┼─────────────────────────┤
│  GNN 30-Day Readmission      │  AUROC +11%        │  Multi-modal EHR        │
│  (Stony Brook Medicine)      │  ████████████████  │  predictive precision   │
├──────────────────────────────┼────────────────────┼─────────────────────────┤
│  U-Net MRI Segmentation      │  Dice Score +14%   │  Surgical planning      │
│  (Published · Sapienza 2023) │  ████████████████  │  boundary precision     │
├──────────────────────────────┼────────────────────┼─────────────────────────┤
│  Published Research          │  1 Paper · 2023    │  Peer-reviewed CV Lab   │
│  (Sapienza / Prof. Pannone)  │  ████              │  Computer Vision + MRI  │
└──────────────────────────────┴────────────────────┴─────────────────────────┘

⚙️   TECHNOLOGY MATRIX



[ 🏥 HEALTHCARE SYSTEMS ]

Epic EHR HL7 / FHIR HIPAA ICD-10 CDS

[ 🧠 AI / MACHINE LEARNING ]

GNN U-Net XAI EHR ML ECG

[ 🧬 BIOINFORMATICS ]

Genomics GATK BLAST Multi-Omics TCGA

[ 📊 VISUALIZATION & ANALYTICS ]

Tableau Power BI Plotly R Shiny Seaborn


🔬   RESEARCH SYSTEMS

🧠   [2025]   Interpretable Deep Learning — ECG-Based Fall Risk Detection
SYSTEM    : XAI Clinical Framework · Fall Risk Stratification in Elderly Inpatients
APPROACH  : ECG time-series → PyTorch model → SHAP explainability layer
OUTCOME   : 70.99% accuracy — every prediction comes with a clinician-readable rationale
STACK     : Python · PyTorch · ECG Signal Processing · SHAP · Clinical Validation
IMPACT    : Clinicians can interrogate predictions — not just receive a black-box score
🕸️   [2024–2025]   Graph Neural Networks — 30-Day Hospital Readmission · Stony Brook Medicine
SYSTEM    : Heterogeneous Graph Neural Network on Multi-Modal EHR Data
INPUT     : Patient history · Lab results · Diagnoses · Procedures (as graph nodes)
OUTCOME   : AUROC +11% over clinical baseline scoring systems
PROGRAM   : Biomedical Informatics · SUNY Stony Brook · Built within Stony Brook Medicine
STACK     : Python · PyTorch Geometric · Epic EHR · Graph Construction Pipeline
🫁   [2023 · Published]   U-Net MRI Segmentation — Sapienza Computer Vision Lab
SYSTEM    : Enhanced U-Net for Clinical MRI Tumor Boundary Segmentation
DATA      : 1 TB of multi-modal imaging data · Processed via Snakemake on HPC Cluster
OUTCOME   : Dice Score +14% · Used for precision surgical planning
PUBLISHED : Under Prof. Daniele Pannone · Sapienza University of Rome · October 2023
STACK     : Python · PyTorch · Snakemake · HPC Cluster · Medical Imaging Pipeline

📊   GITHUB INTELLIGENCE

  






🏅   CERTIFICATIONS & CREDENTIALS

     



     



"I work where genomics meets GPU clusters — making healthcare as intelligent as it deserves to be."
                                                                        — Mittal Kumar

   

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  1. stanford-developers/mittal-kumar stanford-developers/mittal-kumar Public

    biomedicl informatics