Press Release
Asensus Surgical Announces Machine Learning and Cloud Infrastructure Collaboration with Google Cloud to Advance Performance-Guided Surgery
Performance-Guided Surgery can help surgeons perform procedures more accurately and efficiently, and ultimately help surgeons avoid complications and improve patient outcomes.
“We are thrilled to be collaborating with Google Cloud to realize and scale our Performance Guidance Surgery capabilities, by leveraging the data collected by our state-of-the-art ISU technology in conjunction with Google Cloud’s leading machine learning technologies and cloud architecture,” said
The ISU is a real-time intraoperative surgical image analytics platform that leverages augmented intelligence to help reduce surgical variability and provides tools to reduce a surgeon’s cognitive fatigue while collecting clinical data related to the surgical procedure. Asensus will enable customer access portals and performance dashboards for surgeons and hospitals, and Google Cloud’s secure cloud data architecture will capture this data. Asensus will use Google Cloud’s machine learning technologies to analyze the data and discern clinical intelligence that can be utilized by surgeons and hospitals in addition to continuously improving the software in the ISU to provide better intra-operative clinical insight.
“Asensus’ expertise in real-time intraoperative tools combined with our expertise in secure data-capture and machine learning will give surgeons advanced insights to help them in their important work,” said
Additional details on this partnership will be provided at Asensus Surgical’s previously announced investor day that will take place at
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Forward-Looking Statements
This press release includes statements relating to Asensus Surgical’s announcement of its machine learning and cloud infrastructure collaboration with Google Cloud to advance Performance-Guided Surgery. These statements and other statements regarding our future plans and goals constitute "forward looking statements" within the meaning of Section 27A of the Securities Act of 1933 and Section 21E of the Securities Exchange Act of 1934, and are intended to qualify for the safe harbor from liability established by the Private Securities Litigation Reform Act of 1995. Such statements are subject to risks and uncertainties that are often difficult to predict, are beyond our control and which may cause results to differ materially from expectations and include whether the collaboration between
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Source: Asensus Surgical, Inc.