Is there a safety-net effect with computer-aided detection?

Current Available Computer-Aided Detection Catches Cancer but Requires a Human Operator

“…Artificial intelligence-based algorithms improving upon the current CAD would require further research in addition to further investigations into how its implementation in a clinical setting affects patient care. McKinney et al support this by noting that clinical trials are needed for AI; however, they believe that AI has a role in the future in aiding early detection of breast cancer once refined [ 1 , 7 , 14 , 15 ]. McKinney et al’s [ 15 ] study illustrated that CAD is capable of excellent results in controlled testing, but the opposite may occur in real-world scenarios due to various factors including, but not limited to, the radiologists ignoring or misusing CAD due to the high frequency of marks detected that showed no signs of cancer [ 3 , 4 , 7 , 14 ] which result in a large number of callbacks [ 7 , 14 ].…”

“…Regarding CAD’s effect on radiologist’s reads, Du-Crow et al [ 1 ] showed that observer sensitivity was significantly greater for markers detected by CAD compared to the same markers without CAD (t51=6.56, p<0.001); with no significant difference between no-CAD and CAD conditions on markers that were not detected by CAD. This shows that CAD itself may play a significant role in augmenting the radiologist’s ability as a tool.…”

“…As society becomes more advanced, so does the technology that accompanies it; as software and the field of artificial intelligence and machine learning begin to evolve, so must society. The most significant point against automation’s progress is the idea that it can replace the complex human role in the process [ 1 , 2 ]. In the field of diagnostic radiology there is a common distrust in Computer-Aided Detection (CAD) with the underlying reasons ranging anywhere from it being a somewhat recent addition to the field in the early 2000s to CAD’s seemingly inability to consistently provide a benefit to the radiologist [ 3 , 4 ].…”

“…However, while CAD has seen noticeable improvements in accuracy, it could be argued that it remains in its infancy 20 years after its introduction. With that in mind, should CAD be partnered with a radiologist to emulate a double read, the overall theoretical cost could remain low [ 1 , 10 , 11 ]. This would allow an increase in volume to be adopted by the overseeing radiologist [ 1 , 10 , 11 ].…”

“…With that in mind, should CAD be partnered with a radiologist to emulate a double read, the overall theoretical cost could remain low [ 1 , 10 , 11 ]. This would allow an increase in volume to be adopted by the overseeing radiologist [ 1 , 10 , 11 ]. If efficiently implemented into the healthcare system, this increase in volume could accelerate the decrease in breast cancer mortality by expanding access to high‐quality preventive care at a fraction of the cost [ 5 , 6 , 8 , 12 , 13 ].…”