The Viz.ai start-up company was founded in 2016 by entrepreneurs Dr. Chris Mansi, a neurosurgeon, and Dr. David Golan. The technology of the Viz company was developed following a tragic case in which Dr. Mansi lost a patient after a complex brain surgery that was performed successfully, but performed late.
Viz.ai’s innovative and advanced technology is designed to detect medical conditions and diseases such as stroke, cerebral hemorrhage, cerebral aneurysm, pulmonary embolisms, and aortic rupture in real-time. The advanced application, developed by the company, combines the capabilities of artificial intelligence technology to monitor and analyze scans and imaging test results in real-time, to shorten the time interval between imaging testing and treatment significantly, and to immediately alert about diseases and medical conditions, including life-threatening conditions, thus significantly increasing the patient’s chances of recovery.
Speeding up receipt of appropriate treatment in various emergency situations
Time is a critical factor when treating patients in emergency situations such as stroke, cerebral hemorrhage, pulmonary embolism and more. In many emergency situations, the patient must undergo a brain CT or another test to diagnose his condition and determine the correct and optimal treatment for him.
Therefore, it is worth knowing that the Viz.ai company’s AI-based medical solution is designed to shorten processes by early and real-time identification of medical conditions and abnormal findings in imaging tests, and transfer the information to medical teams in various hospitals, in order to expedite and adjust the treatment process. Thus, doctors can essentially make better decisions, and many patients owe their lives to the above technological solution.
It should be noted that Viz.ai’s innovative and advanced system has proven itself in many cases, around the world. For example, the director of the MRI Institute at the Western Galilee Medical Center in Nahariya, Israel, installed the Viz app on his mobile phone, and the app sent him an urgent alert after a CT scan performed on a patient who complained of severe headaches and had been sent for a non-urgent brain CT. In these cases, it is customary to provide an answer to the patient within one to two weeks, but the app detected an emergency situation due to cerebral hemorrhage, and the director of the institute immediately called the patient who was still close to the hospital, and asked him to return to the ward urgently to undergo additional imaging tests. The following day, it was decided that surgery would be performed urgently, to save the patient’s life – surgery which included, among other things, draining of a blood clot.
Artificial Intelligence-Based Platform for Real-Time Disease Detection and Tailoring of Health Care
Viz’s innovative platform uses artificial intelligence and is based, among other things, on state-of-the-art algorithms in the areas of computer vision and deep learning. The system compares the scan to the hundreds of thousands of CT scans included in the database in order to identify patterns and detect diseases and medical conditions that require prompt treatment without delay. The advanced platform catalogs the scans and sends a real-time alert of abnormal findings so that doctors can make correct decisions in real time, without missing any detail along the way. Further, the system is able to send the information between different hospitals, so that the medical staff can refer the patient to the medical center that is most suitable for the required treatment.
By passing on the information and identifying findings and patterns in the CT scan, it is possible to significantly reduce the time between interpretation of the scan and receipt of treatment, thus significantly improving the patients’ chances of recovery.
Viz.ai is improving the platform, and the system is currently suitable for identifying additional diseases apart from strokes; there is also a new feature suitable for clinical trials. One of the system’s advantages is the possibility of integrating with other systems such as clinic management software, including a computerized medical file.
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