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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

WE ARE EAGER TO APPLY OUR EXPERIENCE TO HELP YOUR BUSINESS GROW

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Muteki Groupは、ソフトウェア開発企業であり、8年間でスタートアップや企業向けに100以上のAIプロジェクトを実行し、成功してきました。80名以上のメンバーで構成されるプロフェッショナルチームはプロジェクトの全段階をカバーします。拠点はウクライナ、ポーランド、エストニア、日本、カナダ、アラブ首長国連邦にあります。

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