Lots of sun exposure and other factors can add up to skin cancer that usually is treatable. Unfortunately, a recent reliance on advanced technology to diagnose melanoma conditions might be more flawed than initially thought. New York and New Jersey residents may be interested in the developments.
Image analysis likely flawed
A potential medical malpractice case might arise due to an incorrect melanoma diagnosis made using convolutional neural networks, or CNN, that analyze melanoma tumors. The CNN technology is a collection of deep-learning algorithms that classify and assess data presented in digital images. The systems are nearly as accurate as analysis by a skilled dermatologist but are subject to partial failures that could lead to incorrect medical diagnoses.
Improper classifications lead to false diagnoses
The CNN systems are prone to improper classifications of melanoma types, which could lead to additional medical issues. Some researchers say the CNN systems cannot discern rotational image alterations or altered color balance, which can lead to improper classifications and incorrect medical diagnoses that skilled dermatologists likely would not make. The researchers cited the system’s inability to differentiate between a primate and a panda as an example of obvious errors that no dermatologist would make.
Proper scrutiny required for best results
Ultimately, the CNN technology provides great assistance in melanoma diagnosis, but dermatologists must ensure accurate analysis prior to giving a medical diagnosis. The expert review helps to eliminate obvious errors that could trigger a misclassification of a melanoma lesion and lead to malpractice claims.
When a patient has been subject to improper melanoma diagnosis, an attorney who is experienced in medical malpractice claims may review the matter. The attorney may help the patient gather evidence to present the best possible case for compensation.