AI Helps Clinicians to Make Quick and Accurate Decisions
Healthcare is witnessing adoption of various technologies, right from diagnostics to patient’s treatment. Artificial intelligence are one of these technological trends that is used in various practices in diagnostics. Continuous technological developments for the medical devices, rising infrastructure developments, and increasing investments for automation in practices are some of the main factors demanding the implementation of AI in diagnostics.
AI-based techniques are proved helpful for various applications ranging from automated diagnosis, volume estimation, and accurate measurements to advanced procedure planning and in-op guided tracking. AI-based medical ultrasound modules help to automate the most important measurements including Ejection Fraction, CO, EDA, and EDA. These modules evaluate the performance of main heart functions like motion of the valves and walls. Plus, it not only detects but also classifies abnormalities.
RSIP Vision announced a new set of AI-based medical ultrasound modules. In its press statement, Dr. Rabeeh Fares, Radiologist; Department of Diagnostic Radiology, Sourasky Medical Center, Tel Aviv, Israel said, “Ultrasound is extremely user dependent and can be challenging to interpret. These innovative AI modules help medical teams make quick and accurate clinical decisions and lower the dependence on teams’ experience”.
In recent years, inorganic strategic activities such as mergers & acquisitions, partnerships and collaborations have been witnessed in the market. Industry analyst opine that these activities help companies for the expansion of business around the globe.
But there are also many companies performing organic growth strategies such as product approvals, such as patents and events. For instance, Qure.ai announced last month that it has received its first US FDA 510(k) clearance for head CT scan product ‘qER’. Qure.ai claims that this newly approved qER suite will be able to triage nearly all critical abnormalities visible on routine head CT scans.
About qER, Chief Medical Officer of vRad, Benjamin W. Strong, MD, stated, “Our target turnaround time for emergent studies is 30 minutes but leveraging AI for acutely critical conditions enables us to shorten that time. For conditions such as intracranial hemorrhage, time is of the essence and those precious minutes can be life-changing for our patients. We have done extensive validation of the Qure.ai qER solution and are excited to continue to partner with Qure.ai and improve care for our patients”.
Looking at the transformations in the diagnostics, market research analysts predict that companies delivering the AI solutions in the diagnostics will experience lucrative growth opportunities in the next few years with the rising demand from the global market.
Neha writes articles on sectors including medicine, food, materials, and science & technology. A qualified statistician, she has the ability to observe and analyze the trends in global markets and write compelling articles that help CXOs in decision making. She is a bookworm and loves to read fiction, lifestyle, science and technology. Neha comes with 6 years of experience in content writing and editing that involves blog writing, preparation of study materials and OERs.