Natural Language Processing (NLP)
We implemented advanced NLP algorithms to analyze vast volumes of unstructured medical records, extracting relevant information such as patient demographics, medical history, and eligibility criteria.
Collaborating with a leading pharmaceutical company, our team leveraged cutting-edge AI technologies to revolutionize clinical trial screening. This initiative was aimed to streamline and accelerate patient selection for trials while ensuring precise matching of candidates with study criteria.
We implemented advanced NLP algorithms to analyze vast volumes of unstructured medical records, extracting relevant information such as patient demographics, medical history, and eligibility criteria.
Our AI models employ predictive analytics to assess patient characteristics against trial requirements. This involved the development of a robust predictive model using machine learning algorithms, allowing for real-time predictions of patient eligibility.
To overcome data silos and ensure seamless integration with various healthcare systems, we implemented semantic interoperability. This enabled the AI system to understand and interpret diverse data formats and standards, fostering efficient data exchange.
The screening process automation led to cost savings, minimizing manual efforts. Also, the integration of advanced technical solutions optimized the patient recruitment process.
Pharma
Europe
1 Project Manager, 2 AI Engineers, 1 Developer
AI Predictive Models
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