DermaSensor

DEN230008

DermaSensor Inc. · granted 2024-01-12 · product code QZS · General and Plastic Surgery

Premarket evidence — what FDA accepted

Device typehardware with ml
source quote (p.2)
The DermaSensor device (hereinafter referred to as 'DermaSensor', or the 'DermaSensor device'; Figure 1) utilizes optical spectroscopy and an artificial intelligence/machine learning (AI/ML) based software algorithm to analyze an intact skin lesion to which the device is non-invasively applied.
Algorithmproprietary ML-derived classifier algorithm that analyzes optical recordings of backscattered light (Elastic Scattering Spectroscopy - ESS) to assess for melanoma, squamous cell carcinoma, or basal cell carcinoma.
source quote (p.3)
In the DermaSensor device, analysis of the optical recordings of backscattered light over the range of wavelengths is carried out using a proprietary ML-derived classifier algorithm. The spectrum of scattered intensity vs. wavelength is a pattern, which is analyzed by a proprietary classifier algorithm in the device's built-in microprocessor to assess for the potential presence of melanoma, squamous cell carcinoma, or basal cell carcinoma.
Adaptive (vs locked)No
PCCPNo
Cybersecurity addressedYes
source quote (p.6)
Software documentation and testing, including cybersecurity information, demonstrates that the software will operate in a manner described in the specifications. The hazard analysis characterized software and cybersecurity risks, including device malfunction, measurement-related errors, sensor, cable and other hardware failures, and unauthorized access by malicious end users.

Validation studies (5)

Bench

sample size not stated

endpoints: demonstrate that the device performs as expected under the anticipated conditions of use

standards: ISO 10993-1, ISO 10993-5, ISO 10993-10, ISO 10993-12, AAMI TIR12:2010, AAMI TIR30:2011 (R2016), ETSI EN 301 489-17, IEC 60601-1-2, IEC 60601-1, IEC 62133-2, IEC 62471, IEC 60601-1-6, IEC 60601-2-57, IEC 62304, ISO 14971

Retrospective clinical

n=1,005 patients · 22 site(s)

endpoints: DermaSensor sensitivity compared to that of the study physicians; sensitivity + specificity > 1; DermaSensor sensitivity compared to a performance goal of 90%

Reader study (MRMC)

n=50 cases

endpoints: aided sensitivity superiority to unaided sensitivity; aided sensitivity + specificity >1

Reader study (MRMC)

n=136 cases

endpoints: aided AUROC non-inferiority for all skin cancers; aided reader sensitivity non-inferiority for all skin cancers; aided reader sensitivity non-inferiority for melanoma; specificity non-inferiority margin of 20%

Reader study (MRMC)

n=100 cases

endpoints: aided AUROC non-inferiority for all skin cancers; aided reader sensitivity non-inferiority for all skin cancers; aided reader sensitivity non-inferiority for melanoma; specificity non-inferiority margin of 20%

Reported performance (3 observations)

sensitivity95.5CI 91.7%-97.6%
source quote (p.18)
All malignant lesions - sensitivity 95.5% (91.7%-97.6%)
specificity20.7CI 18.5%-23.1%
source quote (p.18)
Benign lesions - specificity 20.7% (18.5%-23.1%)
aurocas written: “auc0.7896
source quote (p.18)
The area under the receiver operating characteristic (ROC) curve (AUROC) for the device was 0.7896.

Each value carries its own analysis unit and task — never compare or pool across devices. Source: De Novo decision summary PDF.

Predicate network

Postmarket — what happened after clearance

Not yet tracked — the weekly postmarket refresh hasn't snapshotted this device.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to De Novo AI/ML devices in the General and Plastic Surgery panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/DEN230008