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Full-Text Articles in Medical Genetics
Immunohistochemical Pattern– A Prognostic Factor For Synchronous Gastrointestinal Cancer, Catalin Alius, Catalin Gabriel Cirstoveanu, Cristinel Dumitru Badiu, Valeriu Ardeleanu, Vasile Adrian Dumitru
Immunohistochemical Pattern– A Prognostic Factor For Synchronous Gastrointestinal Cancer, Catalin Alius, Catalin Gabriel Cirstoveanu, Cristinel Dumitru Badiu, Valeriu Ardeleanu, Vasile Adrian Dumitru
Journal of Mind and Medical Sciences
Recent advancements in medical genetics and molecular biology are reflected in the modern understanding and approach to colorectal carcinoma (CRC). Understanding the cellular mechanisms and mutational patterns that promote carcinogenesis could enhance the predictive accuracy of the TNM classification. Furthermore, this will allow for a much more documented stratification and tailored oncological treatment. This paper presents an illustrative case of a relatively young patient (50 years old) with no family history of cancer who was diagnosed with four synchronous gastrointestinal (GI) adenocarcinomas displaying a wild type P53, negative BRAF testing, and mutated MLH1 and PMS2 proteins. This case report contributes …
A Novel Methodology To Identify The Primary Topics Contained Within The Covid-19 Research Corpus, Allen Crane, Brock Freidrich, William Fehlman, Igor Frolow, Daniel W. Engels
A Novel Methodology To Identify The Primary Topics Contained Within The Covid-19 Research Corpus, Allen Crane, Brock Freidrich, William Fehlman, Igor Frolow, Daniel W. Engels
SMU Data Science Review
In this paper, we present a novel framework and system for the identification of primary research topics from within a corpus of related publications, the classification of individual publications according to these topics, and the results of the application of our framework and system to the COVID-19 Open Research Dataset (CORD-19). CORD-19 is a corpus of published peer reviewed and pre-peer reviewed articles related to the coronavirus that causes COVID-19. Using machine learning techniques, such as Non-negative Matrix Factorization for Natural Language Processing and a Bayesian classifier, we developed a novel framework and system that automatically extracts sparse and meaningful …