The Ophthalmic EvidenceEngine

Throughout healthcare, the fragmentation of patients’ health data is a persistent challenge, with more than 80% of critical information remaining unstructured, siloed, and difficult to access.¹ By relying on disparate systems that fail to communicate, physicians and healthcare providers struggle to deliver comprehensive care in an efficient manner. To solve this problem, we at Amaros made it our mission to transform ophthalmology by converting complex data into precision intelligence to enhance clinical efficiency and patient outcomes.

We developed the EvidenceEngine, a proprietary data intelligence platform that integrates multiple sources of critical healthcare data into a unified system that enables health care professionals to make faster, more informed decisions.

A Unified Approach to Healthcare Data

The EvidenceEngine combines electronic health records (EHR), provider notes, multimodal imaging, claims data, and even genomic data (when available) to create a unified, searchable database that empowers clinicians with precise real-world analysis and actionable insights (Figure). Think of it as the connective tissue that binds together otherwise disjointed information into a single, coherent picture.

For example, by integrating data from multiple imaging sources such as OCT, SLO, and fundus photography, we can generate a clearer, more holistic view of a patient’s condition.

Human + AI Collaboration

Our approach isn’t about replacing healthcare professionals, it’s about collaboration. By blending the power of artificial intelligence (AI) with human expertise, we deliver insights that simplify clinical workflows. From medical directors to front-desk staff, every user receives information tailored to their needs in order to improve efficiency without adding complexity.

One of the standout features of our platform is its ability to identify “needle in a haystack” patients—those who are at risk but might otherwise be overlooked. For example, via imaging biomarkers, we can identify patients with stages of diabetic retinopathy and diabetic macular edema who haven’t visited the clinic in months, and thereby create opportunities to prevent irreversible vision loss. By harnessing data to proactively identify at-risk patients, healthcare providers can intervene earlier to improve patient outcomes significantly.

Additionally, in multiple case studies, our platform has helped optimize clinical trials by identifying eligible patients five times faster than manual screening. This capability reduced recruitment costs and accelerated the development of new therapies. Achieving such high accuracy and efficiency is made possible by our holistic, robust, and self-improving AI models, which are designed for both image and text processing.

Commitment to Data Privacy

In today’s world, privacy is paramount. Our platform is built with privacy at its core, ensuring both HIPAA and GDPR compliance. We never share clinic data with any third party, even if it has been de-identified and anonymized. By maintaining data as close to its source as possible and delivering only analytical outcomes, we uphold the highest standards of patient privacy while still enabling valuable precision insights.

Looking to Transform Ophthalmology

The future of healthcare is AI-driven with humans in the loop, and the future of ophthalmology is being redefined by platforms like EvidenceEngine. Our technology is built to integrate, simplify, and enhance the way healthcare providers leverage data to improve patient outcomes. We aim to remove the obstacle of fragmented healthcare data and forge a pathway to better-quality care. By transforming the way ophthalmic practitioners use data, we can change the future of vision care.

1. Hyoun JK. Healthc Inform Res. 2019;25(1):1–2. doi: 10.4258/hir.2019.25.1.1.

For more information: https://amaros.ai/

For inquiries, contact Ben Toker at ben@amaros.ai