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

A new report by CSA reveals that rapid developments in AI, ML, and data mining have allowed technology and health care innovators to create intelligent systems in order to optimize and improve the diagnosis process, quickly capturing unforeseen patterns within complex and large datasets.

According to the Agency for Healthcare Research and Quality, 10% of patient deaths are a direct consequence of misdiagnosis. By using AI and ML, health care service providers can improve the precision of each diagnosis. Medical diagnostics using AI and ML are rapidly expanding, and automation is increasingly helping to detect life-threatening conditions in their earliest stages.

For example, ML helps oncologists not only pinpoint the location of a tumor, but can also accurately determine if it’s malignant or benign in milliseconds. Although computer-based predictions aren’t error-free, new research has indicated that its accuracy of classification hovers around 88%. ML can also aid oncological diagnosis and treatment by improving the precision of blood and culture analysis, mapping the diseased cells, flagging areas of interest, and creating tumor staging paradigms.

In dermatology, AI is used to improve clinical decision-making and ensure the accuracy of skin disease diagnoses. ML can aid dermatological diagnosis and treatment by using algorithms that separate melanomas from benign skin lesions. Furthermore, by employing tools that track the development and changes in skin moles, algorithms are used to pinpoint biological markers for acne, nail fungus, and seborrheic dermatitis.

AI can also assist in the diagnosis of ophthalmologic conditions. Some of the latest innovations that these health care centers have adopted are AI-driven vision screening programs, allowing identification of diabetic retinopathy as well as providing physicians with treatment insights and early-stage diagnosis of macular degeneration.

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

Read the full report by CSA.