Consider the Promises and Challenges of Medical Image Analyses Using Machine Learning

Medical imaging saves millions of lives each year, helping doctors detect and diagnose a wide range of diseases, from cancer and appendicitis to stroke and heart disease. Because non-invasive early disease detection saves so many lives, scientific investment continues to increase. Artifical intelligence (AI) has the potential to revolutionize the medical imaging industry by sifting through mountains of scans quickly and offering providers and patients with life-changing insights into a variety of diseases, injuries, and conditions that may be hard to detect without the supplemental technology. Images are the largest source of data in healthcare and, at the same time, one of the most challenging sources to analyze. Clinicians today must rely mainly on medical image analysis performed by overworked radiologists and sometimes analyze scans themselves. The interpretations of medical data are being made mostly by a medical expert. In terms of image interpretation by a human expert, it is entirely limited given its subjectivity, the complexity of the image, the extensive variations that exist across different interpreters, and fatigue. Despite constant advances in the medical imaging space, almost one in four patients experiences false positives on image readings. This can lead to unnecessary invasive procedures and follow-up scans that add cost and stress for patients. And while false negatives happen less often, the impact can be catastrophic. The surprisingly high rate of false ...
Source: MDDI - Category: Medical Devices Authors: Tags: Imaging Source Type: news