AbstractIntroduction and objectives : Early detection remains critical for reducing breast-cancer mortality, yet millions of women worldwide, particularly those in low-resource, rural, or underserved communities, face significant barriers to screening. Clinic-based imaging modalities such as mammography, ultrasound, and MRI require specialized infrastructure, trained personnel, and in-person attendance, contributing to persistent underscreening and sometimes late-stage diagnoses. Feminai™ is a disposable, wearable self-breast-examination patch that integrates heat, blood flow, tissue conductivity and density sensing, with AI-driven analysis. This combination holds the potential for greater accuracy in breast cancer screening. This study evaluates the device's accuracy in identifying abnormal breast findings based on standard mammography, diagnostic US and MRI. Methods This prospective, non-interventional validation study enrolled 150 women aged 25–75 undergoing breast-cancer screening at the "Merav" Clinic, Tel Hashomer Hospital. Participants completed a medical questionnaire and underwent a five-minute scan using the Feminai™ wearable patch. All participants underwent standard imaging with mammography, with diagnostic ultrasound or MRI as indicated. The cohort included 75 women with BI-RADS 1–2 (normal) and 75 with BI-RADS 3-5 (abnormal) findings. Sensor-derived heat and tissue conductivity data were analyzed using a proprietary AI algorithm and compared against radiological assessments and biopsy results. Results : Among 150 women (mean age 49 years), screening mammography identified 75 as BI-RADS 1–2, and 75 as BI-RADS 4–5. The Feminai™ device identified 70 of 75 BI-RADS 4–5 cases as suspicious, correctly detecting all biopsy-proven malignant lesions and five benign cases as non-suspicious, corresponding to 96% sensitivity, 82% specificity, and 98% negative predictive value. Among BI-RADS 1–2 cases, 12 were classified as suspicious and are under six-month follow-up. No device-related adverse events were observed, supporting feasibility for self-administered remote screening. Conclusions : The Feminai™ Breast Examination Kit showed high accuracy, particularly in sensitivity and NPV, indicating strong potential as a remote, cost-effective, and user-friendly early-detection tool. By enabling self-administered screening without reliance on specialized facilities, Feminai™ offers a scalable pathway to improve access in rural settings, low-resource communities, and medically underserved populations, groups most vulnerable to delayed diagnosis. Further large-scale validation is warranted, but these findings support its promise as an impactful addition to global breast-cancer screening strategies.
Ilan et al. (Sun,) studied this question.