Advancing Precision Medicine: Abartys Health Publishes in Scientific Reports

Innovating Reference Interval Estimation with AI

In the article, “Indirect reference interval estimation using a convolutional neural network with application to cancer antigen 125 (CA-125),” Abartys Health presents a groundbreaking deep learning method. This model improves the accuracy of reference interval estimation, specifically for CA-125, a biomarker crucial for detecting ovarian cancer.

The study applied this model to a large dataset of CA-125 results from Puerto Rican women, uncovering significant age-dependent variations in CA-125 levels. These findings suggest the need to revise standard reference limits, enhancing early detection and personalized treatment strategies.

The Power of Big Data and Advanced Analytics

The research underscores Abartys Health’s commitment to leveraging big data processing and advanced analytics on AWS cloud infrastructure. By combining clinical expertise with cutting-edge AI, Abartys Health is driving advancements in precision medicine and improving patient outcomes.

“This study exemplifies how deep learning can transform clinical data into actionable insights, paving the way for more accurate and personalized healthcare.”

– Abartys Health Research Team

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Why This Matters

The findings emphasize the potential of AI and machine learning to refine diagnostic tools, optimize treatment plans, and improve healthcare delivery. This aligns with Abartys Health’s mission to enhance healthcare data interoperability and enable data-driven decision-making.

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Here the link to the research