Reaching an accurate diagnosis is a critical first step in the treatment process. Whether a patient has an internal injury or cancer, a physician must verify the specific underlying cause of their symptoms to develop the most effective treatment plan possible.
Radiology can be an important component of the modern diagnostic process. Imaging tests, such as X-rays and MRIs, can locate internal injuries or validate abnormalities and tissue without requiring a surgical biopsy.
Do patients need to worry about an increased risk of diagnostic failures when hospitals and medical professionals use artificial intelligence (AI) to assess imaging tests?
AI errors are common but preventable
Researchers have found that even AI software specifically programmed for the medical sector can fail at any point without clear indications for the medical professionals using the software. AI may hallucinate information. It may also overlook abnormalities that do not conform with the training or software instructions for the AI.
Due to these serious issues, AI should not serve as the sole means of evaluating radiological images and diagnosing patients. Instead, it should dovetail with human review and services.
Professionals should catch any oversights made by AI during their own review of diagnostic images. The failure to integrate appropriate safety checks into the diagnostic process when using AI software is typically the fault of the medical professional or their employer, not the company that produced the AI software.
If overreliance on technology leads to a failure to diagnose, the professionals involved may have committed malpractice. Reviewing diagnostic records, including any oversights made by AI, with a skilled legal team could help those affected by diagnostic mistakes pursue compensation for the losses triggered by those medical errors.