Sep 22, 2023
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Completed
AI solution for analyzing biomedical research articles
$100,000+
7-12 months
United States
10+
Service categories
Service Lines
Artificial Intelligence
Domain focus
Healthcare
Programming language
Python
Frameworks
TensorFlow
Torch/PyTorch
Challenge
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.
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.
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 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.
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.
Results
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
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