Background:Computer vision syndrome (CVS) encompasses a constellation of ocular and extraocular symptoms in computer users who either habitually or compulsively use computers for long periods of time. Electronic devices such as computers, smart phones, and tablets emit blue light (400–490 nm) from their light-emitting diodes and produce electromagnetic fields, both of which interfere with the circadian rhythm.Aim:This study aims to assess the awareness, knowledge, and impact on sleep quality of CVS among medical students.Materials and Methods:This study included 500 medical students. All participants anonymously filled up a pro forma including sociodemographic details and three questionnaires that (a) tested for awareness and knowledge about CVS, (b) tested for CVS, and (c) the Pittsburgh sleep quality index (PSQI), respectively. Data from 463 complete questionnaires were analyzed.Results:The mean (±standard deviation) age of the 463 individuals was 19.55 (±1.04) years. The prevalence of CVS was 77.5%. The prevalence was higher in boys (80.23%) compared to girls (75.87%), but the difference was not statistically significant. Only 34.1% of the medical students were aware of CVS. Good knowledge regarding various aspects of CVS was observed in 22.46% individuals, while 53.99% and 23.56% had average and poor knowledge, respectively. Poor sleep quality was present in 75.49% of individuals with CVS compared to 50.96% of students without CVS; the difference was statistically significant (odd's ratio [95% confidence interval]: 0.338 [0.214–0.531]). All the components of PSQI score, except components 1 and 6, had statistically significantly (P < 0.05) higher values in individuals with CVS as compared to individuals without CVS.Conclusions:There is high prevalence but low level of awareness and knowledge about CVS among medical students. CVS is significantly associated with poor sleep quality in medical students.

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Unique Data mining is the methodology of investigating sets of information and afterward removing the significant information or learning. It is a term equivalent word with learning revelation. The materiality of this survey paper is highlighted by the way that the information mining is an object of exploration in numerous zones. In this paper, past works in range of information disclosure from therapeutic information are checked on. The objective to study this paper is to enhance proficiency, diminish human slip and help therapeutic specialists with enhanced learning. Medicinal information mining is extricating imaginative learning from the restorative information to enhance the proficiency, abatement cost and time and develop choice emotionally supportive network with objective of wellbeing advancement. We have considered papers from 1999 to 2013 with the plan to find learning from restorative information. A sum of six medicinal undertakings: screening, analysis, treatment, forecast, observing and administration are premise for investigation of each one paper and in each one assignment; we considered five information mining methodologies: order, relapse, bunching, affiliation and half and half. For each one assignment, outline and examination are expressed. The current issues and future slants are said. We hope this paper will further help to find new intriguing milestones for future examination.

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