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| # Vrushket More - Projects | |
| ## TheraMind (Featured Research Project) | |
| **Multi-Agent Healthcare Analytics Pipeline** | |
| - **Type**: Research Project, First Author Publication | |
| - **Tech Stack**: Python, LangChain, NLP, Multi-Agent Systems | |
| - **Publication**: Research Square preprint (DOI: 10.21203/rs.3.rs-6787930/v1) | |
| - **Description**: Built a multi-agent healthcare analytics pipeline processing 10,000+ PubMed case reports to surface clinician-ready NSCLC (Non-Small Cell Lung Cancer) clinical evidence | |
| - **Key Achievements**: | |
| - 92% recall for clinical case detection | |
| - 99.7% specificity for accurate classification | |
| - 70% runtime acceleration through optimization | |
| - **Impact**: First author on published research, demonstrating ability to lead complex AI/ML research projects | |
| ## Peeker AI Analytics Platform | |
| **Customer Analytics Dashboard** | |
| - **Type**: Professional Internship Project | |
| - **Tech Stack**: Python, ETL, Analytics, Dashboard Development | |
| - **Company**: Peeker AI (Startup) | |
| - **Description**: AI-powered customer analytics platform with intelligent ETL pipelines and personalization features | |
| - **Key Achievements**: | |
| - Expanded paying customer base by 50% | |
| - Improved personalization accuracy from 80% to 93% | |
| - Built automated ETL pipeline for LinkedIn and email data processing | |
| - **Live Demo**: peeker.ai | |
| ## Self-Driving Cars Model | |
| **Computer Vision for Autonomous Vehicles** | |
| - **Type**: Academic Project | |
| - **Tech Stack**: Python, OpenCV, SVM, Computer Vision | |
| - **Description**: Real-time lane detection and vehicle classification system for autonomous driving | |
| - **Key Achievements**: | |
| - 98% precision in vehicle detection | |
| - 97% recall for accurate classification | |
| - Real-time processing of 720p video streams | |
| - Heat-map based metrics for pattern identification | |
| - **Features**: Lane curvature detection, vehicle offset tracking, temporal smoothing | |
| ## DermWise | |
| **AI-Powered Dermatology Diagnostic Assistant** | |
| - **Type**: Healthcare AI Project | |
| - **Tech Stack**: Deep Learning, Computer Vision, Healthcare AI | |
| - **Description**: AI diagnostic assistant leveraging deep learning for skin condition analysis and classification | |
| - **GitHub**: github.com/vrushketmore/DermWise | |
| ## ClimateWise | |
| **Climate Analytics Platform** | |
| - **Type**: Data Science Project | |
| - **Tech Stack**: Python, Data Analysis, Visualization | |
| - **Description**: Data-driven climate analytics platform with predictive modeling for environmental pattern analysis | |
| - **GitHub**: github.com/vrushketmore/ClimateWise | |
| ## Clash of Trails | |
| **Trail Recommendation System** | |
| - **Type**: Data Science/Web App | |
| - **Tech Stack**: Recommendation Systems, Data Science, Analytics | |
| - **Description**: Interactive trail recommendation system using data science to match hikers with their perfect outdoor adventures | |
| - **GitHub**: github.com/vrushketmore/Clash-of-Trails | |
| ## English to French Translation Model | |
| **Neural Machine Translation** | |
| - **Type**: NLP/HuggingFace Model | |
| - **Tech Stack**: Transformers, NLP, MarianMT, Fine-tuning | |
| - **Description**: Fine-tuned MarianMT model for English to French translation, trained on KDE4 dataset | |
| - **HuggingFace**: huggingface.co/vrushketmore/marian-fine-tuned-kde4-en-to-fr | |
| ## Cross-lingual Summarizer | |
| **Multilingual Text Summarization** | |
| - **Type**: NLP/HuggingFace Model | |
| - **Tech Stack**: mT5, Summarization, Multilingual NLP | |
| - **Description**: MT5-small model fine-tuned for English to Spanish summarization on Amazon reviews dataset | |
| - **HuggingFace**: huggingface.co/vrushketmore/mt5-small-finetuned-amazon-en-es | |
| ## Power BI Dashboards | |
| **Data Visualization Projects** | |
| - **Type**: Business Intelligence | |
| - **Tech Stack**: Power BI, Data Visualization, Analytics | |
| - **Description**: Interactive business intelligence dashboards including Data Professional Survey analysis | |
| - **Features**: Salary insights, job satisfaction metrics, programming language preferences | |
| - **GitHub**: github.com/vmore2/Power-bi | |