AI-powered skin cancer detection at the point of care for rural health
The rural skin cancer crisis
Skin cancer is the most common cancer in the U.S., yet rural patients face a compounding access crisis that delays diagnosis, drives worse outcomes, and strains limited dermatology capacity.
- Less than 10% of dermatologists practice in rural areas[3]
- Average dermatology wait is 34.5 days nationally — often months in rural settings[4]
- Over 70% of skin cancers[1,2] are first evaluated in primary care settings where physicians lack specialized training or objective diagnostic tools for skin lesion assessment
What DermaSensor brings
- Clinical evidence package: Nine peer-reviewed publications, FDA pivotal study data, and outcome benchmarks
- Grant narrative support: Template language positioning DermaSensor within applicable RHTP initiative categories
- Implementation support: Clinical training, workflow integration guidance, and dedicated account support
- Outcomes reporting tools: Data and reporting frameworks aligned with RHTP performance metrics
- Partnership documentation: Ready-to-execute MOU for collaborative RFA submissions requiring partner agreements
DermaSensor — device overview
DermaSensor[TM] is the first FDA-cleared AI-powered skin cancer risk detection device designed for primary care providers.
Regulatory: FDA-Cleared Class II De Novo; FDA Breakthrough Device. Software-aided adjunctive diagnostic devices for use by non-dermatology providers of lesions suspicious for skin cancer.
How it works
- Apply handheld non-invasive device to suspicious lesion
- FDA-cleared AI algorithm analyzes spectral data and delivers skin cancer risk
results in seconds - Instant output: “Monitor” or “Investigate Further” (refer), with the latter results including
a 1-10 confidence score for malignancy likelihood - ~15 minutes of training — rapid deployment across any site and provider
RHTP funding alignment
The RHTP — a $50 billion, 5-year federal initiative — prioritizes:
- Technology-driven solutions for the prevention
and management of chronic diseases - Investment in technologies that promote efficient
care delivery and access to digital health tools
by rural facilities and providers - Payments to health care providers for the provision
of health care items or services - Measurable, outcomes-driven interventions
with trackable data
DermaSensor system and data architecture
DermaSensor’s outcomes measurement approach is grounded in structured previously utilized registry protocols. Selected data from patients previously evaluated for skin lesions suspicious for skin cancer is collected and compared before and after clinician adoption of the DermaSensor device.
All device users automatically generate Device Record Numbers (DRNs), ESS recordings, and spectral scores for each scanned lesion. This data is complemented by non-PHI data from EMR/EHR systems, integrated into a common data repository, and analyzed across 3, 6, 9, 12, 18, and 24-month intervals following device adoption. This framework directly satisfies RHTP performance reporting requirements by generating measurable, trackable evidence of clinical and system-level impact.
Proposed outcome measures
References
- Eisemann N, Waldmann A, Geller AC, et al. Non-melanoma skin cancer incidence and impact of skin cancer screening on incidence. J Invest Dermatol. 2014 Jan;134(1):43-50. doi: 10.1038/jid.2013.304
- Koelink HJ, Kollen BJ, Groenhof F, van der Meer H, van der Heide F, Thio HB, Blanker MH. Skin lesions suspected of malignancy: an inventory of diagnostic accuracy and therapeutic decisions in general practice. BMC Fam Pract. 2014 Jul 3;15:109. doi: 10.1186/1471-2296-15-109
- Vaidya T, Zubritsky L, Alikhan A, Housholder A. Socioeconomic and geographic barriers to dermatology care in urban and rural US populations. J Am Acad Dermatol. 2018;78(2):406-408. doi:10.1016/j.jaad.2017.07.050
- 2022 Survey of Physician Appointment Wait Times and Medicare and Medicaid Acceptance Rates. https://www.merritthawkins.com/trends-and-insights/article/surveys/2022-physician-wait-times-survey/
- Cancer Facts and Figures 2026. American Cancer Society. https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/annual-cancer-facts-and-figures/2026/2026-cancer-facts-and-figures-acs.pdf.
- Johnson MC, Patel P, Ayers A, Spears KM. Resource Management Challenges in Rural Dermatological Care: A Mapping Review. Cureus. 2025;17(1):e77544. 2025 Jan 16. doi:10.7759/cureus.77544
- Petty AJ, Ackerson B, Garza R, et al. Meta-analysis of number needed to treat for diagnosis of melanoma by clinical setting. J Am Acad Dermatol. 2020;82(5):1158-1165. doi:10.1016/j.jaad.2019.12.063
- Merry SP, Croghan IT, Dukes KA, et al. Primary Care Physician Use of Elastic Scattering Spectroscopy on Skin Lesions Suggestive of Skin Cancer. J Prim Care Community Health. 2025;16:21501319251344423. doi:10.1177/21501319251344423
- Hartman RI, Trepanowski N, Chang MS, et al. Multicenter prospective blinded melanoma detection study with a handheld elastic scattering spectroscopy device. JAAD Int. 2023;15:24-31. 2023 Nov 15. doi:10.1016/j.jdin.2023.10.011
- Jaklitsch E, Thames T, de Campos Silva T, Coll P, Oliviero M, Ferris LK. Clinical Utility of an AI-powered, Handheld Elastic Scattering Spectroscopy Device on the Diagnosis and Management of Skin Cancer by Primary Care Physicians. J Prim Care Community Health. 2023 Jan Dec;14:21501319231205979. doi:10.1177/21501319231205979
- Tepedino M, Baltazar D, Hucks C, Chatha K, Zeitouni N. Use of Elastic Scattering Spectroscopy on Patient Selected Lesions that are Concerning for Skin Cancer. Cutis 2022 December; 110(6 Suppl):35-36.
- Ferris LK, Jaklitsch E, Seiverling EV, et al. DERM-SUCCESS FDA Pivotal Study: A Multi-Reader Multi-Case Evaluation of Primary Care Physicians’ Skin Cancer Detection Using AI-Enabled Elastic Scattering Spectroscopy. J Prim Care Community Health. 2025;16:21501319251342106. doi:10.1177/21501319251342106
- Hartman RI, Trepanowski N, Chang MS, et al. Multicenter prospective blinded melanoma detection study with a handheld elastic scattering spectroscopy device. JAAD Int. 2023;15:24-31. 2023 Nov 15. doi:10.1016/j.jdin.2023.10.011
