This research project analyzes gastrointestinal (GI) publications from Digestive Disease Week (DDW) conferences over the past 5-6 years. The study focuses on:
- Tracking changes in abstract publications
- Analyzing the impact of COVID-19 on research trends
- Utilizing GPC-4 Neural Network for data analysis
- Identifying patterns and trends in gastroenterology research
.
├── data/
│ ├── raw/ # Original DDW abstract datasets
│ └── processed/ # Cleaned and processed datasets
├── src/
│ ├── preprocessing/ # Data cleaning and preparation scripts
│ ├── analysis/ # Statistical analysis scripts
│ ├── visualization/ # Data visualization code
│ └── models/ # GPC-4 Neural Network implementation
├── tests/ # Unit tests and integration tests
├── docs/ # Documentation and research notes
│ └── figures/ # Generated figures and visualizations
└── requirements/ # Project dependencies
- Clone the repository
git clone https://github.com/yourusername/IdentifyingResearchTrends.git
cd IdentifyingResearchTrends- Create a virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate- Install dependencies
pip install -r requirements/requirements.txtThe project analyzes DDW publications from 2018-2023, focusing on:
- Abstract submissions
- Research categories
- Author demographics
- COVID-19 related research
- Geographic distribution
- Data Extraction: Automated scraping of DDW abstracts
- Preprocessing: Cleaning and standardizing data
- Neural Network Analysis: GPC-4 implementation for trend identification
- Statistical Analysis: Multi-variable statistical analysis
- Visualization: Generation of figures and trends.
- Aakash Suresh
- Dr. John Clarke
- Stanford University
- DDW Conference Organization