Report: How AI and ML optimize the diagnosis process in health care

Did you miss a session from the Future of Work Summit? Visit our Future of Work Summit on-demand library to stream.


A new report from CSA reveals that rapid growth in AI, ML and data mining has allowed technology and healthcare innovators to create intelligent systems to quickly capture unexpected patterns in complex and large datasets, optimize and improve the diagnostic process.

According to the Agency for Healthcare Research and Quality, the deaths of 10% of patients are a direct result of misdiagnosis. Using AI and ML, healthcare service providers can improve the accuracy of each diagnosis. Medical diagnostics using AI and ML are expanding rapidly, and automation is increasingly helping to detect life-threatening conditions in their early stages.

For example, ML not only helps oncologists determine the location of a tumor, but can also accurately determine whether it is malignant or benign in milliseconds. Although computer-based predictions are not error-free, new research shows that its accuracy of classification is around 88%. ML can also assist in oncological diagnosis and treatment by improving the accuracy of blood and culture analysis, mapping diseased cells, flagging areas of interest, and creating tumor staging patterns.

In dermatology, AI is used to improve clinical decision making and to ensure the accuracy of skin disease diagnosis. ML can help diagnose and treat dermatitis using an algorithm that isolates melanoma from benign lesions of the skin. In addition, algorithms are used to determine biological markers for acne, nail fungus, and seborrheic dermatitis, using tools that track the growth and changes of skin moles.

AI can also help diagnose ophthalmic conditions. Some of the latest innovations adopted by these healthcare centers are AI-powered vision screening programs, which allow physicians to identify diabetic retinopathy as well as insights into treatment and early stage diagnosis of macular degeneration.

More recently, the Covid-19 epidemic has provided a unique opportunity to prove that technologies such as AI and ML can be used for the benefit of all. AI-based algorithms have been used to optimize health care resources, prioritize hospital resource allocation, and assist in the development and distribution of vaccines. From the initial reports of the epidemic in December 2019, to the early predictions of its spread and impact, to the deployment of AI in vaccine development, automation has played a central role in the fight against Covid-19, as well as other serious diseases and conditions.

Read the full report by CSA.

Venturebeat

VentureBeat’s mission is to become a digital town square for technical decision makers to gain knowledge about transformative technology and practices. Our site delivers essential information on data technologies and strategies so you can lead your organizations. We invite you to access, to become a member of our community:

  • Up-to-date information on topics of interest to you
  • Our newsletters
  • Gated idea-leader content and discounted access to our precious events, such as Transform 2021: Learn more
  • Networking features and more

Become a member

Similar Posts

Leave a Reply

Your email address will not be published.