The technological advancements in the global Healthcare industry are hurtling at light speed. As the medical industry is undergoing immense changes, Healthcare OEMs look forward to the growing technological trends to improve all aspects of patient care. Today, Artificial Intelligence (AI) play significant roles in the evolution of the healthcare industry, so much that algorithms can now predict and detect the root cause of a certain disease, making an accurate and timely diagnosis. For example, AI can detect the underlying cause of cancer, which can eventually help pharmaceutical scientists develop new drugs accordingly. In one recent study, published by Healthcare IT News, "Google and medical partners including Northwestern University have unveiled a new AI-based tool that can create a better model of a patient's lung from the CT scan images. This 3-D image gives better predictions about the malignancy of tumors and incorporates learning from previous scans, enabling the AI to help clinicians in spotting lung cancer in earlier stages when it is vastly more treatable".

VA2CS, the European leader in AI-Powered Fall Detection and Prevention, is launching its product at GSA 2019! The solution is already deployed in 2,700 rooms in 6 European countries. Artificial Intelligence uses visual and infrared sensors to automatically detect when a person is falling and trigger alarm to care-givers. A short recording of the fall allows care-givers to understand the reasons for the fall and to take corrective actions. "Most existing solutions based on a press-button pendant or watch are not reliable; people just don't wear them or forget to press the button when the fall happens," says Ramzi Larbi, VA2CS CEO.

Researchers have developed an artificial intelligence system to detect lung cancer on scans that radiologists fail to detect. The AI method can notice specks of lung cancer with about 95 percent accuracy compared with 65 percent by radiologists, according to research conducted by the University of Central Florida's Computer Vision Research Center. The researchers published their findings in the Cornell University Library before the Medical Image Computing and Computer Assisted Intervention Society's conference next month in Granada, Spain. Computed tomography, or CT, scans use computer-processed combinations of many X-ray measurements taken from different angles to produce cross-sectional images of specific areas of a scanned area. "I believe this will have a very big impact," Ulas Bagci, an engineering assistant professor at UCF, said in a press release.