Applying AI and Machine Learning to Personal Health Challenges
I never planned to become a LARS patient advocate or build health tracking systems. I wanted to focus on my data science career and build innovative AI solutions. But LARS changed my priorities, and I realized I could use my technical skills to fight back.
My Background & Expertise
I'm a data scientist and AI researcher with expertise in machine learning, predictive modeling, and healthcare analytics. When LARS entered my life in December 2023, I applied the same rigorous analytical approach I use professionally to understand and manage my condition.
š¤ Machine Learning & AI
Specialized in predictive modeling and pattern recognition
Random Forest & XGBoost algorithms
Neural networks for health data
Time series analysis
Feature engineering for medical data
š Data Science & Analytics
Expert in turning complex data into actionable insights
Python, R, SQL for healthcare analytics
Statistical modeling and hypothesis testing
Data visualization and dashboards
A/B testing and experimental design
š„ Healthcare Technology
Bridging the gap between technology and patient care
HIPAA-compliant system design
Patient-generated health data (PGHD)
Digital health tool development
Medical research methodology
š” Innovation & Problem Solving
Creating novel solutions for complex health challenges
Product development from concept to launch
User experience design for patients
Privacy-preserving analytics
Scalable system architecture
365+
Days of LARS Data Collected
50+
Variables Tracked Daily
78%
AI Model Prediction Accuracy
200+
Research Papers Analyzed
My LARS & Data Science Journey
December 2023
Surgery & LARS Diagnosis: Underwent colorectal surgery. Cancer successfully removed, but developed Low Anterior Resection Syndrome. Decided to approach this analytically from day one.
January 2024
Data Collection Begins: Started systematic tracking of 50+ daily variables including symptoms, food, mood, sleep, weather, and activities. Built initial database schema.
March 2024
First Insights: Discovered significant correlations between food timing and symptoms. Statistical analysis revealed patterns invisible to casual observation.
June 2024
AI Model Development: Built first machine learning model to predict difficult days. Achieved 78% accuracy using Random Forest algorithm with 15 key features.
September 2024
Research Deep Dive: Analyzed 200+ scientific papers on LARS using AI tools. Built knowledge base and started developing AI-powered Q&A system.
December 2024
Platform Launch: Launched this website and began building community platform. Started sharing tools and insights with other LARS patients.
What I've Built
Over the past year, I've developed several data-driven tools and insights specifically for LARS management:
š ļø Technical Stack & Tools
Data Collection
Custom mobile app, wearable APIs, manual entry systems
Machine learning system that predicts my difficult days with 78% accuracy, helping me plan activities and manage expectations.
Random Forest algorithm with 15 features
Time-series cross-validation
Real-time daily predictions
Confidence intervals and feature importance
š Pattern Recognition System
Automated analysis that identified hidden correlations between seemingly unrelated factors like weather pressure and symptoms.
Correlation analysis and significance testing
Lag effect detection (24-48 hour delays)
Seasonal pattern identification
Multi-variate interaction effects
š Interactive Analytics Dashboard
Real-time visualization of trends, improvements, and setbacks with statistical significance testing and exportable reports.
Time series visualizations
Correlation heatmaps
Progress tracking with trend analysis
Doctor-friendly PDF reports
š¤ AI Research Assistant
Trained on 200+ LARS research papers to provide instant, evidence-based answers to patient questions with citations.
Natural language processing
Research paper analysis and summarization
Confidence scoring for answers
Automatic citation generation
My Data-Driven Philosophy
I believe that patients can use data science to better understand their conditions and improve their outcomes. My personal LARS journey has shown me that:
š Data Empowers Patients
Systematic tracking and analysis reveal patterns invisible to casual observation, giving patients more control over their condition.
š¤ Technology Bridges Gaps
AI and machine learning can fill the space between medical appointments, providing continuous insights and support.
š¬ Community Data Advances Care
Privacy-preserving aggregation of patient data can reveal patterns that help everyone while protecting individual privacy.
šÆ Precision Medicine for All
Every patient can build their own "precision medicine" approach using personal data and machine learning.
Data science gave me the tools to understand LARS. Patient experience gave me the motivation to never give up. Together, they're helping me reclaim my life one data point at a time.
- My Personal Mission Statement
The Vision: Democratizing Health Data Science
I'm building tools and platforms that combine my technical expertise with lived patient experience. The goal is to create data-driven solutions that help LARS patients worldwide:
š® Predictive Health Analytics
Help patients predict and prepare for difficult days using personalized machine learning models.
šøļø Privacy-Preserving Community Insights
Enable collective learning from patient data while maintaining complete individual privacy protection.
š§ AI-Powered Patient Education
Make complex medical research accessible through AI-generated summaries and personalized Q&A systems.
š± Integrated Health Ecosystems
Connect wearables, apps, and medical records into comprehensive health monitoring systems.
Current Projects
Community LARS Tracker: Advanced tracking system with AI insights for the LARS community
Research Analysis Platform: AI-powered tool for analyzing and summarizing medical research
Predictive Modeling Framework: Open-source tools for chronic condition self-tracking
Privacy-Preserving Analytics: Federated learning system for community health insights
Healthcare Data Standards: Advocating for better patient-generated data integration
Important: What This Is and Isn't
This is not medical advice. I'm not a doctor - I'm a data scientist sharing my personal experience and the technical tools I've built for my own condition management. Every strategy I share is my personal experience, not a prescription for anyone else. Always consult with qualified healthcare professionals for medical decisions.
Connect With Me
If you're interested in the technical aspects of what I'm building, want to collaborate on LARS research, or are a fellow data scientist facing health challenges, I'd love to connect.
Let's Build the Future of Patient-Driven Healthcare
Together, we can prove that data science and patient experience make a powerful combination for improving health outcomes.
IMPORTANT LEGAL DISCLAIMER: I am not a medical professional. This website shares my personal experiences with LARS only and does not constitute medical practice, advice, diagnosis, or treatment in any jurisdiction. This is not a medical service. All content represents personal opinions and experiences only. Always consult qualified, licensed healthcare providers for medical decisions, advice, and treatment. For medical emergencies, contact emergency services immediately. Use of this website does not create a doctor-patient relationship.