Our Solutions
Patient-centered outcome measures
Routes to diagnosis and care pathway
Evolution of patient experience
Online health boards are a valuable source of the patient voice, where patients (and carers) share first-hand information about their lived experience, symptoms, response to treatment, and unmet needs.
Mebomine’s unique data analytics methodology combines domain-specific natural language processing, machine learning and statistical analysis to find, interpret and link clinical insights from online patient communities about thousands of conditions, supporting a wide variety of needs.
Maryam is a data scientist at the Barts Cancer Institute. Her research includes machine learning with applications in bioinformatics and health informatics.
Conrad is the chair of Bioinformatics at Queen Mary University of London. He has over 25 years’ experience developing analytics solutions for the life sciences.
Fabrizio is an associate professor of Artificial Intelligence at Queen Mary University of London. He is an expert in machine learning with over 20 years’ experience.
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