document: LungCAD : a clinically approved , machine learning system for lung cancer detection We present LungCAD , a computer aided diagnosis ( CAD ) system that employs a classification algorithm for detecting solid pulmonary nodules from CT thorax studies . We briefly describe some of the machine learning techniques developed to overcome the real world challenges in this medical domain . The most significant hurdle in transitioning from a machine learning research prototype that performs well on an in-house dataset into a clinically deployable system , is the requirement that the CAD system be tested in a clinical trial . We describe the clinical trial in which LungCAD was tested : a large scale multi-reader , multi-case ( MRMC ) retrospective observational study to evaluate the effect of CAD in clinical practice for detecting solid pulmonary nodules from CT thorax studies . The clinical trial demonstrates that every radiologist that participated in the trial had a significantly greater accuracy with LungCAD , both for detecting nodules and identifying potentially actionable nodules ; this , along with other findings from the trial , has resulted in FDA approval for LungCAD in late 2006 .
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