Artificial intelligence (AI) and machine learning(ML) have helped optimize processes and workflows in many industries. In the healthcare sector, AI is increasingly helping in solving tough problems and uncovering hidden insights in the data generated by hospitals most of which is unstructured.Read More
The early detection of diseases is crucial in the process of improving a patient’s health. However, this task can be time-consuming and complex, especially since many serious ailments can present themselves as the common cold or the flu in their early stages. The high demand for specialists that are able to discern illnesses causes many issues in early detection of diseases because they are often focused on more high profile cases. By using an ML system for predictions, we can drastically improve a patient’s chances of survival, in both pneumonia detection and other cases where radiology is necessary for early detection.
Computer vision technology is one of the many solutions to the issue of early diagnosis for serious diseases that may not present themselves as serious. A specific type of computer vision technology, called image classification technology, is the process that Skyl, a machine learning platform, used to automatically label whether or not an X-Ray image of a lung is one with pneumonia. Skyl has used it’s platform to create this project. It uses a deep learning methods, ensuring each prediction becomes more accurate as it receives more data. However, image classification technology is not limited to a single class, there could be multiple different categories that an image falls under. For example, a picture could contain a dog, cat, or fish. In this particular case, there were only two categories, pneumonia and not pneumonia.
The Skyl Solution
Using Skyl, healthcare professionals can input data various from sources that have labeled data. For the lung project, Skyl used pre-labeled data from the National Institutes of Health Clinical Center. Using only this data and our platform, Skyl successfully created a project and we were able to train the algorithm, and deploy it on our website. However, this is only one example of how Skyl’s platform can be used. Image classification technology in the healthcare industry has been used to diagnose different forms of cancer, check for fractures in X-Rays, and process MRI scans. By automatically moving certain cases to a higher priority, doctors, nurses, and radiologists waste less time ignoring patients who may have serious ailments.
The uses of image classification technology are not limited to the healthcare industry and radiology. The same software that classifies images can classify any type of unstructured data which includes audio, video, and images. This technology has been used to analyze satellite images and deforestation, find explicit words in music, and detect faces. We have only dipped our toes in the future of image classification technology and how it will affect the future of the way businesses, schools, hospitals, and our day-to-day lives are conducted. Certain companies, such as Skyl, are dedicated to making sure that every company on the planet can create a machine learning project, because we do not have all the ideas, other people do! We just hope to get enterprises to a point that their ML dreams can become a reality and not just a fun idea in the office.
Skyl.ai is a SaaS platform that allows any business to streamline a computer vision or natural language processing project. Visit Skyl.ai to learn more about the future of computer vision technology and how it can impact your business!