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Introduction: Early diagnosis is the key in the prevention of transformation of oral mucosal lesions into life threatening disease 'CANCER', hence the need of the study determines the prevalence and site distribution of Oral Mucosal Lesions in patients attending outpatient department of Shivam Dental Clinic, Lakhimpur. Methods: A cross-sectional prevalence study was carried out to assess the prevalence and site distribution of Oral Mucosal Lesions in patients attending outpatient department of Shivam Dental Clinic, Lakhimpur. The sample size was estimated to be 150. A single examiner previously trained for the diagnosis of Oral Mucosal lesions made all examinations. The data was collected using the WHO oral health assessment form 2013. The data analysis was done using the SPSS version 20. Result:The results stated a strong association between age, chewing tobacco smoking and oral lesions. Conclusion:The present study concludes a positive relation between intake of tobacco in any form with oral mucosal lesions hence an additional effort to educate the masses about the hazardous effects of tobacco should be a priority for both governmental and non-governmental agencies.

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Introduction: Artificial Intelligence is a branch term for all the developing systems, furnished with human intelligence. Even though Artificial Intelligence can be useful in field of  dentistry and can be of help in dental office but is not used extensively. A gap exists in the knowledge regarding application  of Artificial Intelligence in Dental offices.  Therefore, the present study was carried to determine the factors associated with knowledge and perception regarding use of Artificial Intelligence in dentistry among the dental professionals. Methodology: A cross sectional study was carried on 362 dental professionals of North India. A non-probability Snowball  sampling was used. A The face validity and content validity was done for forming the questionnaire  of the present study. The final questionnaire consisted of 13 variable, structured, close-ended questionnaire in English of which 7 were knowledge-based, 4 were based on attitude and 2 based on practice.  SPSS version20 was used for statistical Analysis. Frequency, percentage was calculated. Chi-Square test was applied to determine factors associated with knowledge attitude and practice of Artificial Intelligence. A spearman’s correlation and Multiple logistic regression was run to assess the corelation between knowledge and practice of AI by the dentist. Statistical significance was kept at p value<0.05.