BeNeXT: AI to Detect Turner Syndrome
Detecting Turner Syndrome earlier—and more accurately—is not just a medical challenge: it is an opportunity to transform the lives of thousands of girls and women worldwide.
This vision is becoming real with BeNeXT, a research initiative that combines artificial intelligence, multiomics analysis, and student talent to achieve earlier, more precise, and more accessible diagnosis.
And yes, it’s just as powerful as it sounds.
What Is Turner Syndrome and Why Is Early Detection Important?
Turner Syndrome is a genetic condition caused by the total or partial absence of one X chromosome. It can affect growth, physical development, fertility, and cardiovascular health.
But here’s the real issue:
In many cases, diagnosis can take up to 15 years.
This leads to late interventions, prolonged uncertainty, and missed opportunities to improve patients’ quality of life.
Did you know…
Early diagnosis of Turner Syndrome enables interventions that significantly improve patients’ physical, emotional, and social development.
Technology, Health, and Research in One Project
BeNeXT was born within the HER (Human Environment Research) line at our campus, led by Dr. Xavier Sevillano. Its purpose is clear: to create new tools to support early and personalized detection of Turner Syndrome.
What Makes BeNeXT Unique?
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AI applied to health: advanced facial analysis to identify phenotypic patterns associated with the syndrome.
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Multiomics data: integration of genetics, phenotype, and clinical markers to identify subtypes of the syndrome.
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A personalized approach: moving toward faster, more specific, and patient-tailored diagnoses.
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Young talent participation: students from the Health Engineering degree collaborate in the project, learning real research and contributing new perspectives.
Innovation That Matters: How the BeNeXT Approach Works
AI and Facial Analysis
Artificial intelligence makes it possible to detect subtle patterns that may go unnoticed to the naked eye. Using models trained on images and clinical data, BeNeXT aims to identify early indicators of the syndrome.
Multiomics Analysis
The integration of genetic, molecular, and clinical data helps better understand the diversity within Turner Syndrome.
This means:
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more accurate diagnoses
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identification of clinical subtypes
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better medical decisions from early ages
Did you know…
The combination of AI + multiomics is one of today’s most powerful trends in personalized medicine. BeNeXT applies it directly to a real-world case.
Project Impact: Benefits for Patients, Science, and Society
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Reduced diagnostic delay
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Better planning of treatments and clinical follow-up
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Increased visibility for a lesser-known condition
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Boost to technology-driven research in healthcare
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Student participation, gaining real skills in biomedical research, AI, and data analysis
BeNeXT and La Salle: Research, Collaboration, and Future
This project positions us as leaders in health-applied research, combining artificial intelligence, biomedical innovation, and talent development.
The active participation of students from the Health Engineering degree turns the project into a direct bridge between learning and research, allowing them to work with real data, emerging technologies, and challenges that are shaping the future of healthcare.
Because ultimately, BeNeXT is not only about detecting Turner Syndrome earlier. It’s about proving that when technology, science, and education come together, solutions that change lives are born.
HEALTH ENGINEERING AT | LA SALLE-URL