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AmCAD-UO is an innovative solution to assist physicians evaluating the risk of Obstructive Sleep Apnea (OSA) syndrome. The solution consists of a positioning system and a computer-assisted detection (CAD) software device. The positioning system helps accurately locate the ultrasound probe to scan and acquire multiple-angle sonographic images of the upper airway. The computer-assisted detection software device is to automatically detect the airspace of the pharyngeal airway. The dynamic changes of the airspace are then computed to evaluate the risk of OSA. The evaluation process is performed on awake patients and takes no more than 10 minutes to get the results. The entire process is objective, accurate, cost-effective and safe and is expected to transform the clinical practice of OSA diagnosis.
About AmCad BioMed Corporation
AmCad BioMed Corporation (AmCad) was founded in 2008 and was listed on Taipei Exchange in the March of 2015 (Ticker: 4188). Our breadth of expertise, from R&D to commercialization, have resulted in world’s first FDA cleared ultrasound Computer-Assisted Detection (CAD) devices. AmCad is committed to assisting medical professionals in making efficient and accurate diagnosis through the support of detailed sonographic visualization and quantification. By integrating AI technology with clinicians' expertise, AmCad will continue to pioneer best-in-class imaging solutions that anticipate mainstream medical needs.
When it comes to ultrasound examination for thyroid, different physicians may arrive at different interpretations over the same image; the inconsistency of the results may reach up to 70%. Even though physicians made a definitive diagnosis and thus performed thyroidectomy, up to 50% of results turned out to be benign. Unfortunately, life-long medication is required for patients who have undergone thyroidectomy.
A reliable approach is needed for the physicians to make faster and more effective interpretations and thus avoid unnecessary thyroidectomy.
AmCAD-UT utilizes patented image analysis technology to capture clinical diagnostic features of thyroid neoplasm from 2D ultrasound images. Through quantification and visualization, detailed color images are thereby displayed for substantially improved and more accurate medical ultrasound interpretation.