Biometric identification is the study of physiological and behavioral attributes of an individual to overcome security problems. Finger vein recognition is a biometric technique used to analyze finger vein patterns of persons for proper authentication. This paper presents a detailed review on finger vein recognition algorithms. Such tools include image acquisition, preprocessing, feature extraction and matching methods to extract and analyze object patterns. In addition, we list some novel findings after the critical comparative analysis of the highlighted techniques. The comparative studies indicate that the accuracy of finger vein identification methods is up to the mark.

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Diabetic retinopathy (DR) is a complication of diabetes that exists throughout the world. DR occurs due to a high ratio of glucose in the blood, which causes alterations in the retinal microvasculature. Without preemptive symptoms of DR, it leads to complete vision loss. However, early screening through computer-assisted diagnosis (CAD) tools and proper treatment have the ability to control the prevalence of DR. Manual inspection of morphological changes in retinal anatomic parts are tedious and challenging tasks. Therefore, many CAD systems were developed in the past to assist ophthalmologists for observing inter- and intra-variations. In this paper, a recent review of state-of-the-art CAD systems for diagnosis of DR is presented. We describe all those CAD systems that have been developed by various computational intelligence and image processing techniques. The limitations and future trends of current CAD systems are also described in detail to help researchers. Moreover, potential CAD systems are also compared in terms of statistical parameters to quantitatively evaluate them. The comparison results indicate that there is still a need for accurate development of CAD systems to assist in the clinical diagnosis of diabetic retinopathy.

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Aim: Rheumatoid arthritis (RA) is a chronic progressive disabling disease that mainly affects joints. Studies documenting Pakistani patients' knowledge regarding RA disease are lacking and there is a need for such endeavor. The purpose of this study was to develop and validate a novel research tool to document patient knowledge about RA disease. Methods:A novel research instrument known as the rheumatoid arthritis knowledge assessment scale (RAKAS) which consisted of 13 items, was formulated by a rheumatology panel and used for this study. This study was conducted in rheumatology clinics of three tertiary care hospitals in Karachi, Pakistan. The study was conducted in March-April 2018. Patients were recruited using a randomized computer-generated list of appointments. Sample size was calculated based on item-to-respondent ratio of 1:15. The validities, factor structure, sensitivity, reliability and internal consistency of RAKAS were assessed. The study was approved by the institutional Ethics Committee.Results: A total of 263 patients responded to the study. Content validity was 0.93 and response rate was 89.6%. Factor analysis revealed a 3-factor structure. Fit indices, namely normed fit index (NFI), Tucker Lewis index (TLI), comparative fit index (CFI) and root mean square of error approximation (RMSEA) were calculated with satisfactory results, that is, NFI, TLI and CFI > 0.9, and RMSEA < 0.06. Internal consistency (α) was 0.62, that is, acceptable. All items had a high discrimination index, that is, >19 and difficulty index <0.95. Sensitivity and specificity of RAKAS were above 90%.