Bibliometric Study on Analysing Impact of newly launched products over existing ones through AI

Different analysis models like Conditional Mean Analysis, Trend Analysis, Correlation Analysis helps us to analyse the delicate equilibrium between businesses that gets impacted when a new product is launched in a cluster. This paper shows a statistical report of research done on the businesses in a cluster based on ongoing trends and current customer needs . There is surplus data present on various platforms related to every product following the ongoing trends in the form of customer reviews.The research mainly speculates mainly how the businesses get impacted with change in consumer needs, wants and demands. With the help of datasets that are available from online sources incorporating various machine learning techniques which would help us analyze the correlation of two businesses and by checking on various algorithms for analyzing the results obtained regarding the study made covering various aspects of businesses. On top of that, the precision largely depends on the evaluating parameters that are taken into consideration along with finding helpful patterns in those evaluating parameters to characterise the main problem. In this report, to perform bibliometric analysis Scopus Database is employed. This bibliometric analysis considers essential keywords, datasets, and significance of the selected research papers. Moreover it offers details regarding types, sources of publications, yearly publication trends, affiliations and so on from Scopus. Furthermore, it captures details concerning co-appearing keywords, authors, titles of sources through networked diagrams. From this research paper it is perceived that there is a lot of research for the considered research area. This kind of research will also be helpful for speculating how the new businesses impact the awareness of the customers on the existing ones

Integrative Analysis Identifies Four Molecular and Clinical Subsets in Uveal Melanoma

Comprehensive multiplatform analysis of 80 uveal melanomas (UM) identifies four molecularly distinct, clinically relevant subtypes: two associated with poor-prognosis monosomy 3 (M3) and two with better prognosis disomy 3 (D3). We show that BAP1 loss follows M3 occurrence and correlates with a global DNA methylation state that is distinct from D3-UM. Poor-prognosis M3-UM divide into subsets with divergent genomic aberrations, transcriptional features, and clinical outcomes. We report change-of-function SRSF2 mutations. Within D3-UM, ElF1AX- and SRSF2/SF3B/-mutant tumors have distinct somatic copy number alterations and DNA methylation profiles, providing insight into the biology of these low- versus intermediate -risk clinical mutation subtypes