According to researchers, medical errors of various types may be the third-leading cause of death in North Carolina and across the country. Various efforts to introduce artificial intelligence to the healthcare environment are often spurred on by an attempt to cut down on patient risks caused by human error. These machines often enjoy exceptional performance; one found in Oxford is reportedly capable of exceeding cardiologists' success rate in identifying a patient's risk of a potential heart attack.
Other types of artificial intelligence at use in the medical field include machines that diagnose skin cancer, identify a vision-threatening eye problem or recognize types of lung cancer. However, just as AI raises new potential for accuracy, it also raises new concerns about errors of a different type. Some medical mistakes may be caused by the machine or its algorithm rather than a specific physician or surgeon. It may not be immediately clear who is at fault if a machine fails to diagnose a patient or, in later iterations, improperly performs a surgery.
Partially because of these concerns as well as the current state of the technology, most machines in medicine today are meant to assist, rather than replace, the independent professional judgment of a physician. This means that the doctor using and directing the equipment is responsible for errors that negligently put the patient at risk; other questions may be raised if inaccurate machine coding is responsible for a false reading or report.
When people go into the hospital or seek out medical treatment, they expect to receive thorough care at a professional standard. When doctors fail to diagnose cancer or perform an inappropriate surgery or treatment, patients can suffer severely worsened medical conditions. People who have been injured as a result of a physician's mistake might work with a medical malpractice attorney to pursue compensation for their ensuing damages.