A Comparison of Initial and Subsequent Follow-Up Strobovideolaryngoscopic Examinations in Singers.

OBJECTIVES: Previous studies have identified abnormal findings in up to 86.1% of singers on initial screening strobovideolaryngoscopy (SVL) examinations. No studies have compared the prevalence of abnormalities in singers on their subsequent follow-up SVL. Our study evaluates the frequency of these findings in both the initial and subsequent examinations. METHODS: Retrospective charts and SVL reports were reviewed on students from an opera conservatory from 1993 to 2014. All students had initial screening SVL, but only students who later returned with acute voice complaints were included in the study (n = 51, 137 follow-up visits). Normal SVL was defined as an examination without structural or functional abnormalities and reflux finding score ≤7. Data were analyzed using the chi-square test. RESULTS: For initial examinations, 90.2% (including reflux) and 88.2% (excluding reflux) were abnormal. In follow-up examinations, 94.9% (including reflux) and 94.2% (excluding reflux) had abnormal findings, which included muscle tension dysphonia (40.1%), vocal fold (VF) masses (unilateral 48.9%, bilateral 30.7%), vascular abnormalities (unilateral 27.0%, bilateral 5.8%), sulcus (unilateral 17.5%, bilateral 5.1%), VF hypomobility (unilateral 36.3%, bilateral 5.9%), phase (30.6%) and amplitude (44.8%) asymmetries, and glottic insufficiency (49.3%). Follow-up examinations revealed a significant increase in laryngopharyngeal reflux (χ(2) = 7.043; P \u3c 0.05). CONCLUSIONS: We found a higher prevalence of abnormal findings compared with previous studies, which we attributed to a more inclusive definition of abnormal pathologies, improvements in SVL technology, and possibly increased experience with SVL interpretation. This high prevalence of abnormal findings in asymptomatic singers further supports the importance of baseline examinations

Faculty Convocation 1994

Faculty Convocation at Morehead State University Faculty Convocation in 1994

Tracking Dirty Proceeds: Exploring Data Mining Technologies As Tools To Investigate Money Laundering

Money laundering enforcement operations in the USA and abroad have developed in the past decade from the simple use of informant information to the sophisticated analysis of voluminous, complex financial transaction arrays. Traditional investigative techniques aimed at uncovering patterns consume numerous man-hours. The volume of these records and the complexity of the relationships call for innovative techniques that can aid financial investigators in generating timely, accurate leads. Data mining techniques are well suited for identifying trends and patterns in large data sets often comprised of hundreds or even thousands of complex hidden relationships. This paper explores the use of innovative data mining methodologies that could enhance law enforcement’s ability to detect, reduce, and prevent money laundering activities. This paper provides an overview of the money laundering problem in the USA and overseas and describes the nature and scope of the money laundering problems. It reviews traditional approaches to financial crime investigation and discusses various innovative data mining and artificial intelligence-based solutions that can assist financial investigators