Reveal for Lung Cancer

Reveal lung cancer risks hiding in plain sight

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Up to


More cases of lung cancer found with Reveal for Lung Cancer

Up to


Screening efficiency for lung cancer with Reveal.



Of lung cancer cases flagged in a typical cohort of screening-eligible patients.



Of patients with higher risk apparent risk targeted with Reveal.

AI-powered lung cancer detection

Lucem Health Reveal for Lung Cancer uses a proven AI algorithm to analyze your existing EHR data and identify patients who are more likely to present with lung cancer.

Allowing you to treat lung cancer patients earlier, when outcomes are better and total treatment costs are lower.

Deliver more proactive lung cancer care

Only 6.5% of eligible adults undergo recommended lung cancer screening, and part of why 45% of non-small cell lung cancer diagnoses occur at Stage 4, when the 5-year survival rate is only 9%. Reveal for Lung Cancer creates new opportunity for you to target priority patients for screening.

Reveal for Lung Cancer:

  • Uses standard EHR data and a proven AI model to flag ever-smokers 40-89 years old who have higher statistical risk for lung cancer.

  • Risk-stratifies patients for additional engagement, including those who meet USPSTF lung cancer screening guidelines.

  • Enables you to target patients for earlier diagnosis and treatment.

  • Optimizes utilization of lung cancer screening resources that may be scarce.

Reveal for Lung Cancer Graphic

No changes to clinical workflow

Straightforward implementations

Secure and scalable technology

Real return from targeted screening

Consider a population of 58,000 adults meeting USPSTF lung cancer screening criteria. The following scenarios compare the first two years of programs with and without Reveal for Lung Cancer, which targets the 10% of patients flagged for higher apparent risk of lung cancer.

Projected Clinical Benefit

Projected amount of patients with Non-Small Cell Lung Cancer (NSCLC) identified in the first two years using Reveal for Lung Cancer.

With Reveal*

365 patients

*Projected patients diagnosed, 9-12 months earlier than typical diagnosis

Without Reveal**

86 patients

**Expected lung cancer diagnoses from opportunistic screening

Projected Financial Benefit

Projected treatment acceleration in the first two years based on improving detection of Non-Small Cell Lung Cancer (NSCLC).

With Reveal*

$34 Million

*Treatment revenue accelerated, based on 9 months earlier detection

Without Reveal**

$1.3 Million

**Additional costs driven by higher rate of Stage 4 diagnosis

Why Reveal for Lung Cancer?

Deliver timely Dx and treatment

Reveal for Lung Cancer flags patient risks 9-12 months prior to when they would otherwise be diagnosed. With earlier identification, about 15% of Stage 4 cases could instead be identified at Stages 0-3.

Improve patient outcomes

Lung cancer has a 65% survival rate when diagnosed at localized stage, compared to 9% survival rate when diagnosed at Stage 4.

Effectively target higher risk patients

In a typical cohort of screening-eligible patients, Reveal is expected to flag nearly 50% of lung cancer cases.

Enhance clinical yield

With Reveal, find a projected 370% more cases of lung cancer compared to opportunistic USPSTF screening of an equal-size patient cohort.

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From Partners You Can Trust

Lucem Health partnered with Medial EarlySign to develop the Reveal for Lung Cancer solution.

About Medial EarlySign 

Medial EarlySign’s clinical machine learning software solutions help healthcare stakeholders keep patients healthier longer. Healthcare clients derive actionable and personalized clinical insights from massive amounts of health data leading to potential improvements in quality care, outcomes, diagnostic efficiency, and to accelerate the latest advances in drug research and therapy. EarlySign’s AlgoMarkers and predictive solutions can help clients select enriched subpopulations and more accurately identify and prioritize patients for multiple conditions for interventions to halt or prevent the serious complications from the onset of disease or optimize clinical trials design and recruitment. The company’s purpose-built development environment enables fast, accurate, and explainable models supported by peer-reviewed research published by internationally recognized health organizations and hospitals.

Early Detection Saves Lives

Bring the power of clinical AI to your organization today—so you can reveal hidden patient risks, focus your resources, and deliver higher clinical value, more proactive patient care.

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