Doctors in Texas may soon get relief from their heavy caseloads in the form of artificial intelligence. Past AI symptom checkers were only able to provide medical information, offer triaging advice and make possible diagnoses based on correlation alone. Because correlation is not causation, these AI systems haven’t been able to make a definitive diagnosis.
Now, a group of Babylon scientists has developed a causal learning machine that may help. The machine has a powerful algorithm that allows it to look at different diseases that could be presenting certain symptoms in the patient. In early tests, the machine scored higher than 70% of doctors who took written exams.
This new development is exciting medical personnel around the world. An estimated 50% of people across the world don’t have access to health care. While an AI machine can’t replace a physician, it could help physicians reach and treat people using existing health care systems. Some experts also believe it could help reduce medical malpractice claims. Over 12 million people across the United States receive an incorrect diagnosis each year, and 33% of these individuals suffer a severe injury due to an incorrect diagnosis. AI may be able to help doctors correctly diagnose their patients and reduce injuries and death.
Fatalities due to medical mistakes kill more than 250,000 people each year, making them the third leading cause of death in the United States. There is a high demand for doctors and nurses across the country, and a lack of doctors means that many doctors have a high patient load and must see and diagnose a patient within a few minutes. This could lead to incorrect diagnoses and medical malpractice claims. A lawyer may be able to help a family or individual who was injured because of an incorrect diagnosis. A doctor who behaved negligently might be responsible for compensatory damages to the injured parties.