Raymond Adams

Using AI to Efficiently Diagnose and Reduce Error

Artificial intelligence is taking over the healthcare industry. Although it is known that AI will take many jobs away from workers in many different fields, healthcare is one field where it may be most beneficial. AI has been able to efficiently diagnose and reduce error. An article from Managed Healthcare Executive states, “Human error is the determining factor in 70% to 80% of industrial accidents, as well as in a large percentage of errors and adverse events experienced in healthcare.” In fact, according to built-in, misdiagnosing patients and medical error “accounted for 10% of all US deaths” in 2015.

There are several factors for why human error occurs in healthcare. The first factor is that workers in the industry cannot keep up with the vast amount of new research and recommendations that are regularly being released. According to Managed Healthcare Executive, “In 2010, a new journal article was published to the National Library of Medicine every 40 seconds” and this rate has probably increased since then. The issue here is that no healthcare provider can keep up with the new information that is continuously being written and discovered. Another factor is that humans are prone to cognitive biases that affect the way we solve problems accurately, efficiently, and reliably. Humans also are susceptible to factors such as stress, distraction, and sleep deprivation which all can contribute to human errors.

Artificial intelligence can reduce all of these issues and can efficiently diagnose patients with diseases at rates that humans could never. For example, built-in states, “an AI model using algorithms and deep learning diagnosed breast cancer at a higher rate than 11 pathologists.” Many existing and new companies have begun creating AI software to help resolve these issues that humans just aren’t capable of fixing. PathAI is a company that is developing algorithms to help pathologists produce more accurate diagnoses. Buoy Health is another company that is using AI to check people’s symptoms and provide cures. Buoy has become so useful and reliable that Harvard Medical School is one of the many hospitals that use the AI-based symptom and cure checker.

Zebra Medical Vision is an AI-powered radiology assistant that according to Zebra, “is empowering radiologists with its revolutionary AI1 offering which helps health providers manage the ever increasing workload without compromising quality.” Their goal is to provide radiologists with the tools they need to make the next big improvement in patient care. The need for medical imaging services is constantly growing. Like most fields in healthcare, humans just can’t keep up. The number of radiology reports is out numbering the workers that are able to analyze the reports.

Zebra Medical Vision is solving this problem by having their imagining analytics engine take-in imaging scans from numerous approaches and automatically analyzes the images for multitude of clinical findings. Zebra-Med works by using a large database that contains millions of imaging scans as well as machine learning and deep learning to develop software that according to Zebra-Med, “analyzes data in real time with human level accuracy.”