Academate
As part of my work in applying generative AI and systems biology to tackle complex biomedical challenges, I've developed Academate, an AI-powered tool designed to streamline systematic literature reviews.
This tool addresses the traditionally time-consuming process of title and abstract screening by leveraging the power of Large Language Models (LLMs) like GPT and LLaMA.
What does Academate do?
Automates Screening: Academate uses LLMs to intelligently analyze titles and abstracts, quickly identifying the most relevant papers for a given systematic review.
Enhances Efficiency: By automating the initial screening, Academate dramatically speeds up the review process, freeing up researchers to focus on deeper analysis.
Improves Accuracy: The use of advanced LLMs helps to minimize human error and bias, leading to a more precise and reliable selection of studies.
Why is this important?
Systematic reviews are crucial in scientific research, providing a comprehensive and unbiased summary of existing evidence. Academate makes this essential process faster and more accurate, ultimately accelerating scientific discovery.
My Commitment
Academate reflects my commitment to pushing the boundaries of biomedical research through innovative AI solutions. It demonstrates the potential of LLMs to transform how we process and synthesize scientific information, paving the way for more efficient and impactful research. I plan to continue to develop tools that can help solve problems in the scientific literature, such as: the identification of knowledge gaps and biases, the improvement of scientific writing, and the development of scientific research skills.
Code Availability
Academate code can be found in: Github
For a working demo you can visit: Academate Webtool
Key features based on the provided document
Multi-LLM Benchmarking: Academate allows for performance comparisons across different LLM architectures, ensuring optimal model selection.
Transparency and Reproducibility: Built on the PRISMA framework, the tool promotes rigorous and standardized review methodologies.
User-Friendly Interface: Features like interactive visualizations and a chatbot interface enhance usability and insights.
This project showcases my expertise in:
Natural Language Processing (NLP)
Large Language Models (LLMs)
Systematic Review Methodology
Biomedical Data Analysis
