Images and Cloud Platforms in Medical Centers
Image sharing is changing how we diagnose in the medical industry. These days, patients expect a lot more than they did decades ago. Technology advances in communication have shaped how we deal with information. Cloud-sharing platforms like ImageCoast enable access to data to users across the globe. It is no wonder patients expect the same level of communication from their doctors.
Real-time communication and image sharing are readily available, making it easier for a team of medics to collaborate and provide the correct treatment. Diagnosing as fast as possible reduces frustration, time-wasting, being prescribed the wrong medication, and anxiety. More and more medical centers need images to be accessible to doctors at the same time. Cloud storage platforms enable remote teams to review a case.
AI vs. Doctors: Image Sharing and Scanning Competition
Over the years, image sharing with the use of cloud platforms has meant several things in radiology – in particular; it has enabled researchers to test AI diagnosis recognition against the best doctors in the world. Back in January 2020, AI outperformed a team of doctors in detecting breast cancer. Researchers from Google Health and Imperial College London, designed a computer model to scan X-ray images from nearly 29,000 women. The results revealed that AI performed as well as two doctors working together and the algorithm was faster and better at detecting problems than six radiologists reading mammograms. Women between 50 and 70 are asked to come in for a breast scan every year. AI can scan images in seconds. Many women will be given attention at a faster rate than an individual doctor. It also provides a higher rate of diagnosis. With such a considerable shortage of radiologists globally, AI image-sharing will be revolutionary in the medical industry’s speed of diagnosis and treatment.
Going back two years further to 2018, an AI system developed by BioMind scored 2:0 against top physicians in Beijing. Developers added tens of thousands of images of nervous system-related diseases archived by the Tiantan Hospital over 10 years to train the AI. The competition involved predicting brain tumors and hematoma expansion in patients. The AI system diagnosed 87% of 225 cases within 15 minutes. In contrast, the team of 15 doctors achieved 66%.
By removing some tasks from doctors and allowing a more efficient process to take place, doctors can reduce their workload and put more time on learning and development or digging deeper into an illness that is still untreatable.