The image analysis system rarely

The image-analysis system rarely indicated a false negative classification across OM categories with a negative predictive value of 0.95. Normal TM\'s were only indicated incorrectly in 8% of AOM and 4% of OME and CSOM with perforation. This accuracy is promising since it is similar to and better than reported diagnostic accuracy by pediatricians (Kuruvilla et al., 2013) and GP\'s (Blomgren and Pitkäranta, 2003; Jensen and Louis, 1999). Minimizing false negatives is important to ensure treatment in cases where it is indicated. Over-diagnosis by clinicians, however, is often a problem in AOM (Pichichero and Poole, 2001) and as a result the American Academy of Pediatrics recently prioritized greater diagnostic specificity to reduce over-diagnosis and unnecessary treatment (Lieberthal et al., 2013). The current system in telomerase inhibitor correctly identified AOM in 81.3% of instances. This could support accurate diagnoses at primary health care levels at which skilled clinical assessment is often unavailable or limited. A computer-assisted diagnostic system, such as this, can also provide a useful second opinion to assist health care workers in making correct diagnoses. Benefits include timely initiation of treatment and reduced health system burden related to over-referrals. The custom-made video-otoscope indicated overall clinical diagnostic accuracy of 78.7% compared to 80.6% on images from commercial video-otoscopes. While being assessed on a smaller sample of ears from adults (108) and only three diagnostic categories represented (Table 4) the results suggest that a custom-made video-otoscope could provide a low-cost method for accurate diagnosis of common ear disease. However, future investigations should evaluate the clinical validity in children compared to adults. The accumulated production cost of the custom-designed video-otoscope was around $84, which is at least 5 times less expensive than commercial entry-level video-otoscopes. Of course, as with regular video-otoscopes it still requires a computer to capture images. The computer together with the Matlab® software adds significantly to the cost. It would therefore come to the region of $1000 to operate the complete systems. However, the use of a netbook and the open source equivalent of Matlab®, (i.e. GNU Octave), will bring the cost down to between $250 and $300. The cost of equipment must be seriously considered if a method for automated diagnosis of OM is to be a viable solution for underserved contexts. The present study demonstrates the accuracy of an image analysis system for diagnosis of one of the most common childhood illnesses (World Health Organization, 2004; Global Burden of Disease Study 2013 Collaborators, 2015). In light of the shortage of specialists able to accurately diagnose OM, especially in low and middle-income countries, a system like this could be very valuable to ensure that appropriate treatment is provided. For instance, nurses could be trained to take pictures of the TM using a video-otoscope and analyzed by the image analysis system locally or on a cloud-based server. In many world regions this is likely to be the only opportunity for access to a diagnosis of ear disease amongst large populations. In addition to these applications the system could be employed for teaching and training purposes in diagnosing OM to up-skill general health care workers in diagnosing ear disease.
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Acknowledgments
Introduction Rheumatic heart disease (RHD) and HIV are prevalent in Uganda and other sub-Saharan African countries. Rheumatic heart disease (RHD) affects 15million people worldwide with an estimated 1.4million deaths annually. In Uganda RHD is the most common cause of heart disease within the 15 to 49 age group (Remenyi et al., 2012; Okello et al., 2012; Marijan et al., 2012; Sliwa and Zilla, 2012). The immunopathogenesis of chronic valvular inflammation in RHD including the role of cellular vs. humoral immune responses, and the identity of the responsible immunodominant epitopes that drive the progression of disease are debated (Tandon et al., 2013). HIV currently affects 5–10% of Ugandan adults, which is improved from nearly 30% in the early 1990s (The Republic of Uganda, 2014). The immune deficiency and dysfunction caused by HIV and AIDS has been shown to impact susceptibility to and progression of other autoimmune diseases (Zandman-Goddard and Shoenfeld, 2002); however, the impact of HIV infection on RHD pathogenesis has not been investigated.