ArticleJournal of primary care & community health
DERM-SUCCESS FDA Pivotal Study: A Multi-Reader Multi-Case Evaluation of Primary Care Physicians' Skin Cancer Detection Using AI-Enabled Elastic Scattering Spectroscopy.
Article in Journal of primary care & community health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Artificial Intelligence in Oncology: A Comprehensive Cross-Cancer Translational Readiness Analysis Across 18 Malignancies.Cancers · 2026Review
- From ABCD to AI: Assessing the Diagnostic Reliability of MLLMs in Cutaneous Melanoma Screening-A Head-to-Head Comparison.Diagnostics (Basel, Switzerland) · 2026Article
- Precision Diagnosis in Cutaneous Head and Neck Squamous Cell Carcinoma.Biomedicines · 2026Review
- Enhancing Diagnostic Precision in Primary Care: A Multireader Multicase (MRMC) Study of an AI-Powered Handheld Elastic Scattering Spectroscopy Device for Informed Referral Decisions in Melanoma Evaluation.The Journal of clinical and aesthetic dermatology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundElastic Scattering Spectroscopy (ESS), an optical tissue sampling technique, distinguishes between benign and malignant tissue in vivo without the need to perform a surgical biopsy. A handheld device that employs ESS enabled with an artificial intelligence algorithm was developed as an objective tool to aid primary care physicians (PCPs) in their management of lesions suspicious for skin cancer. The aim of this study was to assess and compare the diagnostic and management performance of PCPs with and without the use of the ESS device in detecting skin cancer.
methodsIn this clinical utility study, 108 PCPs evaluated 100 skin lesion cases (50 aided with the device output and 50 unaided by the device). For each case, PCPs provided a diagnosis, management decision, and level of confidence in that decision initially without, and then subsequently with, device output. Sensitivity, specificity, AUC, and confidence in their assessment prior to, and then with, device output were compared.
resultsWith visual assessment assisted by device output, diagnostic sensitivity increased significantly from 71.1% to 81.7% (
conclusionUse of the ESS device output by PCPs significantly improved their diagnostic and management sensitivities as well as their overall management performance. The findings suggest the ESS device can improve PCP skin cancer detection and confidence in their skin lesion evaluation and management.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.