Dr. Martin FergieABDULAZIZ MOHAMMED ALI SHARAHILI2022-05-292022-05-29https://drepo.sdl.edu.sa/handle/20.500.14154/49424Background: Through digital image analytics, automation, quantification, and objective screening of tissue samples, the capacity to acquire high-resolution digital scans of complete microscopic slides with high-resolution whole slide scanners is altering tissue diagnosis discovery. Digital image analysis has become a well-known term for this field. TIL analysis has also been shown to have prognostic and predictive value in melanoma. Aim of the study: The purpose of our study was to evaluate the QuPath classifier's performance in classifying lymphocytes and tumour cells, as well as to estimate the relationship between TILs and melanoma. Moreover, conduct a survival analysis of clinical data. Material and methods: We developed an algorithm for image-based automated assessment of TILs on haematoxylin-eosin-stained sections in melanoma with an open-source software (QuPath), using a retrospective collection of 70 melanoma patients. Moreover, the data were processed with Microsoft Excel for survival analysis was conducted using SPSS software. Results: We demonstrate that age and gender play a significant role in survival scale of melanoma when men represent the higher percentage than women on death rate. Further, the thickness and metastasis of tumour had also serios impact. Conclusion: QuPath is an open source bioimage analysis tool that is specifically built for entire slide images. We've shown that it has the tools needed for fast, accurate, and repeatable digital pathology investigation in a variety of difficulties. Patients detected at a late stage, an older age, and with thicker melanomas had lower melanoma survival rates. Female patients and those who were younger had greater melanoma-specific survival than men and those who were older, and these differences were statistically significant.en