AI solution for analyzing biomedical research articles
#ML/AI, healthcare
CHALLENGE
The problem was that the amount of published research 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 to automate the analysis process and provide more accurate and efficient results.
CLIENT
Global B2B SaaS company that offers an AI-powered automation platform and services in 50+ countries.
TECHNOLOGY
MongoDB, PyTorch, Python, Tensorflow, Biopython, Scispacy, Biobert, Google Cloud platform
TEAM
Skilled software developers with extensive back-end, Cloud integration, and AI knowledge
INDUSTRY
Healthcare
SOLUTION
Our team of experts developed a deep learning and natural language processing (NLP) system that could extract important terms from the articles, establish relations, and create a summary and knowledge graph of connected terms. The system uses advanced NLP techniques, including Biobert and Scispacy, to analyze the biomedical text accurately.
IMPACT
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 days
●allow medical professionals to make informed decisions about patient care
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Muteki Group is a full-cycle software development company that has successfully completed 100+ AI projects for startups and enterprises since 2015. Our 80+ member team covers everything from the discovery phase to support. We are located in Ukraine, Poland, Estonia, Japan, Canada, UAE, and the USA.
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