A concerning trend shows that global incidence of early-onset cancer increased by 79.1% and the number of early-onset cancer deaths increased by 27.7% between 1990 and 2019*.
With its non-invasive, clinically validated AI solution, EarlySign is working with global healthcare partners to illuminate the path and remove obstacles to early detection of colorectal cancer in populations over the age of 40, in addition to lung cancer in various populations.
These efforts can be particularly effective to address broader populations who may not be aware of the importance of screening, especially as the age for screening is expanding to include those at a younger age.
Effective clinical outreach can highlight ways that early detection delivers benefits for individuals including the possibility of avoiding more invasive procedures, enhancing quality of life, and improving survival rates.
EarlySign was built with a mission to develop a clinical AI platform for early detection of high-burden diseases for those which are likely at risk of complications from serious disease. We are aligned with our care partners to play a significant role in improving more precise and personalized care delivery. Joined by physicians, scientists, and engineers, Medial EarlySign now works alongside global healthcare organizations to help and improve deliver accurate, explainable, and personalized predictive insights for recommending assessment for early detection of potential complications from different diseases and chronic conditions. We partner with our clients to empower them with our capabilities to rapidly deploy sophisticated algorithms for the singular purpose of offering improved enrichment of populations to create focused opportunities for more effective care and support keeping people healthier, for longer.
EarlySign solutions utilize predictive models that can detect individuals more likely to have a serious condition based on ML-based analysis of the information from existing clinical data. The predictive models within the solution connect subtle data points that may not be noticed, nor can they be expressed by simple rules or calculators. Medial EarlySign expertly curates real-world information; transforming raw data into machine learning ready data and then providing actionable person-level insights. The EarlySign machine learning infrastructure is purpose built to overcome the inherent limitations in putting AI to work, leading to meaningful clinical insights when and where you need them most.Â
We closely partner with organizations across the healthcare continuum, and across the globe, to derive and deliver patient-level, actionable insights directly into existing clinical workflows. From diagnostic and pharmaceutical to medical centers and researchers, EarlySign enables informed decision making to identify patients at high-risk for high-burden diseases.
EarlySign’s research is carried out with a rigorous quality methodology to minimize biases while maximizing transferability and explainability. We prioritize and invest resources and effort to independently validate our research in multiple environments leading to recognition and publication in multiple peer-reviewed journals. Our products are developed under strict quality management systems adhering to ISO general and medical device quality standards.
Healthcare clients choose EarlySign because their models work. Additionally, clients benefit from our quality, validated clinical risk predictors, peer-reviewed studies, focus on patient care, and prioritizing clinical workflow. With over 17 clinical papers published in leading medical journals, EarlySign models have been validated with proven accuracy and efficacy. Further, recent findings from the CMS AI Challenge indicate that EarlySign eliminates inherent bias which creates opportunities for early intervention strategies and more effective prioritization of resources.
