Intelligent Machine Caculates Corrects and Verifies Essential Clinical Breast Exam Skills
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Although the earliest symptoms of breast cancer are self-detected lesions or lumps, providers may miss them without verfied skills.
Essential clinical breast exam skills are required to reliably detect the presence of suspicious, self-reported breast lesions and tumors. It was however, impossible to measure and calibrate the skills required for providers’ performance of the exam. In response, the National Science Foundation supported development of a self-administered training technology that calculates and corrects provider performance.
The portable, hands-on trainer plugs into any computer, trains and verifies palpation skills, true and false detections and thoroughness of the exam until built-in standards are met. To our knowledge this is the first transformation of a clinical skill into technology that calculates, corrects and validates competence.
It is now in use training the hands of public health nurses, physicians and midwives. Private mammography clinics have recently begun training and certifying their Breast Radiologic Technicians to perform clinical breast exams.