Abstract: A computerized method of automatically processing a medical imaging record using a machine learning model includes training a machine learning model prediction engine with historical medical imaging records, receiving a first medical imaging record from a first system, applying a set of specified approval criteria to the first medical imaging record to determine a provisional outcome, and in response to the provisional outcome being negative, selectively identifying an exception to the provisional outcome in response to input received by a user interface. In response to the exception not being identified, the method includes inputting a feature vector based on the first medical imaging record to the machine learning model prediction engine to generate a likelihood estimate, comparing the generated likelihood estimate to a target threshold, and in response to the generated likelihood estimate being greater than the target threshold, transmitting a signal indicating approval to the first system.

Abstract: A secondary containment system for containing fuel leaks or leaks of other environmentally hazardous fluids includes a containment chamber and a detection system for detecting leaks. The containment system includes a fluid-carrying inner pipe and a containment pipe surrounding the inner pipe with an interstitial space being defined between the two pipes for containment of leaks. The interstitial space is pressurized with an inert fluid at a constant pressure greater than the pressure of the fluid flowing through the inner fluid-carrying pipe. Monitoring of the pressure of the inert fluid in the interstitial space triggers an alarm indicating that a leak has occurred. The location of the leak can be determined by the use of multiple pressure sensors. The containment pipe is reenforced to withstand pressures of at least 75 psi.