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112 results on '"Abhishek Kathuria"'

1. Endo-Hepatology: The Buzz Goes Much beyond Liver Biopsy—A Narrative Review

Author

Rajesh Puri, Zubin Sharma, Swapnil Dhampalwar, Abhishek Kathuria, and Bimal Sahu

Subjects
endotransplant hepatology, endo-hepatology, EUS-guided liver biopsy, EUS in hepatology, Diseases of the digestive system. Gastroenterology, RC799-869
Abstract

The word endo-hepatology evokes many perceptions. Some believe it to be the emerging new interventional branch and some believe it to be an extension of endoscopy. Nonetheless, it has continued to evolve into an exciting area of active work. With the advent of endoscopic ultrasound (EUS) based procedures, new vistas have opened up. EUS-guided liver biopsies, portal hypertension management, and multiple new procedures are being described. EUS also plays a large role in the management of patients in the peritransplant period. With this review, we present an overview of the role of EUS in the field of hepatology as well as during the peritransplant period and its applications.

Published
2023
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50. ParaCap: paraphrase detection model using capsule network

Author

Anubhav Singh, Anmol Saxena, Rachna Jain, Abhishek Kathuria, and Anjali Khandelwal

Subjects
Authentication, Computer Networks and Communications, business.industry, Computer science, 020207 software engineering, Context (language use), Cryptography, 02 engineering and technology, computer.software_genre, Paraphrase, Computer graphics, Hardware and Architecture, 0202 electrical engineering, electronic engineering, information engineering, Media Technology, Question answering, 020201 artificial intelligence & image processing, Plagiarism detection, Artificial intelligence, business, computer, Spatial analysis, Software, Natural language processing, Information Systems
Abstract

This paper is concerned withthe problem of paraphrase detection. For a number of applications, the ability to detect similar sentences, such as text mining, summary text, plagiarism detection, authorship authentication, and question answering, is important. Given two phrases, the goal is to detect whether they are identical semantically. This work involves a novel model namely, ParaCap, which uses capsule networks for the investigation of sentences. Capsule networks understand the spatial information (context, language, length of sentences and others) by using the instantiation parameters for the better results as compared to CNNs. For the objective, the Quora Question Pair dataset containing 404291 pairs of Quora Questions is being used. The ParaCap model outperforms many state-of-art methods, and also proves to be comparable to other techniques by achieving the accuracy of 89.19%.

Published
2021

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