A retrospective study was carried out on 396 patients who presented with ovarian masses. Sixty five (16%) patients were found to have ovarian malignancy while the rest either had benign ovarian tumours (n = 159), endometriotic cysts (n = 130), physiological cysts (n = 20) or inflammatory masses (n = 7). The relative risk for ovarian malignancy among these patients increased significantly (p < 0.001) after the age of 40 years. The presence of ascites, abdominal distension, urinary complaints and loss of appetite and weight were significant individual risk factors for malignancy. Ultrasound image of a complex cyst is also associated with increased risk of malignancy in an ovarian mass. None of the individual risk factors was discriminatory between a benign and malignant cyst. However, these factors can be combined to form a 20-point risk scoring system. The risk of malignancy in an ovarian cyst increased with increasing scores. In this study, the median scores were 3 for benign cyst, 7 for borderline malignancy and 12 for malignant cysts. Using a total score of 7 as a cut off point, one can detect 75% of malignant cysts with a specificity of 84.1%, a positive predictive value of 47.5% and a negative predictive value of 94.6%. It is concluded that the majority of malignant ovarian cysts can be identified preoperatively to allow arrangement and planning of an optimal surgery.

The Cognitive Tutorial concept is based on the view that the genuine cognitive challenges to forming functional and accurate mental models of AI systems can be formalized, documented, and "trained in." Its purpose is to serve as a means of global explanation of an AI or machine learning system. A Cognitive Tutorial is created specifically to accelerate proficiency at learning to use intelligent software tools. Therefore, it would be a valuable addition to any "toolkit" for ensuring that intelligent systems are explainable, are adequately explained to users, and the users are satisfied with their understanding of the system. This Report describes the procedures for creating a Cognitive Tutorial, the modules that comprise a Cognitive Tutorial, and example Cognitive Tutorials applied to two AI systems.

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