JohnApelJr.github.io/index.html at main · JohnApelJr/JohnApelJr.github.io · GitHub

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  <title>John Apel Jr. — Data Science Portfolio</title>
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<header>
<img class="avatar" src="/assets/profile.jpg" alt="John Apel Jr.">
<h1>John Apel Jr. — Data Science Portfolio</h1>

<div class="links top-links">
<a href="mailto:johnapeljr@gmail.com">Email</a> ·
<a href="https://github.com/JohnApelJr" target="_blank">GitHub</a> ·
<a href="https://linkedin.com/in/john-apel-76700154" target="_blank">LinkedIn</a> ·
<a href="https://johnapeljr.github.io">Portfolio</a>
</div>

<p class="tagline">
Predictive modeling · Deep learning · ETL & data engineering · SQL database design · Process improvement
</p>
</header>

<section>
<div class="grid">

<!-- NEW FLAGSHIP PROJECT -->
<article class="card">
<h3>Healthcare Access Analytics (NC Pediatric Specialists)</h3>
<p class="meta">NPPES · Census ACS · GeoPandas · Folium · GIS</p>
<p>
Built a reproducible geospatial pipeline mapping pediatric specialist supply vs. child population across North Carolina's 100 counties. Identified 67% of counties as severe access deserts and 8 counties with zero pediatric specialists.
</p>
<div class="actions">
<a class="btn" href="https://github.com/JohnApelJr/nc-pediatric-access-pipeline" target="_blank">GitHub repo</a>
<a class="btn" href="https://johnapeljr.github.io/nc-pediatric-access-pipeline/maps/nc_pediatric_access_interactive.html" target="_blank">Interactive map</a>
</div>
</article>

  <!-- NC PRENATAL CARE -->
<article class="card">
<h3>Healthcare Access Analytics (NC Prenatal Care)</h3>
<p class="meta">HRSA AHRF · Census ACS · HPSA · CDC WONDER · GeoPandas · Statsmodels</p>
<p>
Five-source geospatial analysis of prenatal care access across NC's 100 counties; identified 27 counties with zero OB/GYN providers, 96/100 counties with active maternity shortage designations, and a federal surveillance gap that renders all 23 Western NC counties invisible in CDC natality data.
</p>
<div class="actions">
<a class="btn" href="https://github.com/JohnApelJr/nc-prenatal-care-access" target="_blank">GitHub repo</a>
<a class="btn" href="https://github.com/JohnApelJr/nc-prenatal-care-access/blob/main/docs/NC_Prenatal_Care_Executive_Summary.pdf" target="_blank">Executive Summary</a>
</div>
</article>

<!-- DMAIC -->
<article class="card">
<h3>Process Improvement (DMAIC)</h3>
<p class="meta">MBC-638 · Statistics · Six Sigma</p>
<p>Personal fitness optimization using Six Sigma DMAIC, regression, and hypothesis testing; +200 cal/day improvement validated via two-sample t-test.</p>
<div class="actions">
<a class="btn" href="https://github.com/JohnApelJr/JohnApelJr.github.io/tree/main/process%20improvement" target="_blank">GitHub folder</a>
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<!-- SQL DATABASE -->
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<h3>Membership Database (SQL Server)</h3>
<p class="meta">IST-659 · ER/3NF · Triggers · Governance</p>
<p>Normalized 3NF schema (8 entities) with T-SQL triggers and views for LARC (150+ members); migrated from Access → SQL Server for scalability and integrity.</p>
<div class="actions">
<a class="btn" href="https://github.com/JohnApelJr/JohnApelJr.github.io/tree/main/membership%20database/Group2_W2SO_Membership_Database" target="_blank">GitHub folder</a>
</div>
</article>

<!-- GEO ANALYTICS -->
<article class="card">
<h3>Geospatial Analytics (Chronic Disease)</h3>
<p class="meta">CDC PLACES · Census ACS · GeoPandas · Folium</p>
<p>ETL pipeline integrating 2 federal data sources across 2,956 counties; identified 326 "triple burden" counties where diabetes, uninsured rates, and poverty converge.</p>
<div class="actions">
<a class="btn" href="https://github.com/JohnApelJr/chronic-disease-geospatial-pipeline" target="_blank">GitHub repo</a>
<a class="btn" href="https://github.com/JohnApelJr/chronic-disease-geospatial-pipeline/blob/main/notebooks/analysis.ipynb" target="_blank">Notebook</a>
</div>
</article>

<!-- ML -->
<article class="card">
<h3>Machine Learning (Preventive Pulse)</h3>
<p class="meta">CDC BRFSS · scikit-learn · SMOTE · XGBoost · Matplotlib</p>
<p>Heart-disease prediction on 319K+ CDC survey records; logistic regression with SMOTE achieved 83.5% ROC-AUC and 75.7% F1-score across 6 classifiers. Identified age, stroke history, and self-reported health as the dominant risk factors. Applied the trained pipeline to 445K unseen 2022 records.</p>
<div class="actions">
<a class="btn" href="https://github.com/JohnApelJr/Preventative-Pulse" target="_blank">GitHub repo</a>
<a class="btn" href="https://github.com/JohnApelJr/Preventative-Pulse/blob/main/Preventative_Pulse.ipynb" target="_blank">Notebook</a>
</div>
</article>

<!-- DEEP LEARNING -->
<article class="card">
<h3>Deep Learning (Melanoma Detection)</h3>
<p class="meta">HAM10000 · TensorFlow/Keras · EfficientNet-B0 · Grad-CAM · Transfer Learning</p>
<p>Image classifier detecting melanoma from 10,015 dermoscopy images using two-stage transfer learning with EfficientNet-B0. Achieved Macro ROC-AUC of 0.925 across 7 lesion types. Grad-CAM heatmaps visualize model focus regions for clinical interpretability.</p>
<div class="actions">
<a class="btn" href="https://github.com/JohnApelJr/Melanoma-Detection-DL" target="_blank">GitHub repo</a>
<a class="btn" href="https://github.com/JohnApelJr/Melanoma-Detection-DL/blob/main/ISIC_Skin_Lesion_Classification.ipynb" target="_blank">Notebook</a>
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© 2026 John Apel Jr. · <a href="mailto:johnapeljr@gmail.com">Contact</a>
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