We have previously reported an interactive information-theoretic CADe (IT-CADe) system for the detection of masses in screening mammograms. The system operates in either traditional static mode or in interactive mode whenever the user requests a second opinion. In this study we report preliminary investigation of a new paradigm of clinical integration, guided by the user's eye-gazing and reporting patterns. An observer study was conducted in which 6 radiologists evaluated 20 mammographic cases while wearing a head-mounted eye-tracking device. For each radiologistreported location, eye-gazing data were collected. Image locations that attracted prolonged dwelling (>1000msec) but were not reported were also recorded. Fixed size regions of interest (ROIs) were extracted around all above locations and analyzed using the IT-CADe system. Preliminary analysis showed that IT-CADe correctly confirmed 100% of reported true mass locations while eliminating 12.5% of the reported false positive locations. For unreported locations that attracted long dwelling, IT-CADe identified 4/6 false negative errors (i.e., errors of decision) while overcalling 8/84 TN decisions. Finally, for missed true masses that attracted short (i.e., errors of recognition) or no dwelling at all (i.e., errors of search), IT-CADe detected 5/8 of them. These results suggest that IT-CADe customization to the user's eye-gazing and reporting pattern could potentially help delineate the various sources of diagnostic error (search, recognition, decision) for each individual user and provide targeted decision support, thus improving the human-CAD synergy.