AI solution for analyzing biomedical research articles.
Global B2B SaaS company that offers an AI-powered automation platform and services in 50+ countries.
Data scientists and software developers with expertise in deep learning, NLP, and cloud computing.
MongoDB, PyTorch, Python, Tensorflow, Biopython, Scispacy, Biobert, Google Cloud platform
About the project
Our client, a biomedical research organization, approached us with the challenge of analyzing large volumes of research articles in their field.
They needed a solution that could extract important terms, establish relations between them, and create a summary and knowledge graph of connected terms.
The problem was that the amount of research being published was increasing rapidly, and manually analyzing and extracting key information was time-consuming and error-prone. Our solution was to develop an AI-powered system that could automate the analysis process and provide more accurate and efficient results.
Our team of experts developed a deep learning and natural language processing (NLP) system that could extract important terms from the articles, establish relations between them, and create a summary and knowledge graph of connected terms. The system uses advanced NLP techniques, including Biobert and Scispacy, to accurately analyze the biomedical text.
The result was a predictive system that could accurately
analyze doctor notations
determine whether a patient should be included or excluded from a medical program
ML techniques implemented in the system can predict a patient's readmission during the 30-day period
allow medical professionals to make informed decisions about patient care