Enhancing semantical text understanding with fine-tuned large language models: A case study on Quora Question Pair duplicate identification. by Sifei Han, Lingyun Shi, Fuchiang Rich Tsui

“…Semantical text understanding holds significant importance in natural language processing (NLP). Numerous datasets, such as Quora Question Pairs (QQP), have been devised for this purpose. …”
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Resolving ambiguity in natural language for enhancement of aspect-based sentiment analysis of hotel reviews by Asma Nadeem, Malik Muhammad Saad Missen, Mana Saleh Al Reshan, Muhammad Ali Memon, Yousef Asiri, Muhammad Ali Nizamani, Mohammad Alsulami, Asadullah Shaikh

“…Sentiment analysis, a fundamental research task of natural language processing (NLP) is used for mining sentiments and opinions within this vast reservoir of text reviews. …”
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Applications of Deep Learning to MRI Images: A Survey by Jin Liu, Yi Pan, Min Li, Ziyue Chen, Lu Tang, Chengqian Lu, Jianxin Wang

“…Deep learning provides exciting solutions in many fields, such as image analysis, natural language processing, and expert system, and is seen as a key method for various future applications. …”
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Perceptions in 3.6 Million Web-Based Posts of Online Communities on the Use of Cancer Immunotherapy: Data Mining Using BERTopic by Xingyue Wu, Chun Sing Lam, Ka Ho Hui, Herbert Ho-fung Loong, Keary Rui Zhou, Chun-Kit Ngan, Yin Ting Cheung

“…The textual data were preprocessed by natural language processing. BERTopic modeling was performed to identify topics from the posts. …”
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Efficient Method for Robust Backdoor Detection and Removal in Feature Space Using Clean Data by Donik Vrsnak, Marko Subasic, Sven Loncaric

“…These methods target different areas, such as computer vision (CV), natural language processing (NLP), and thus utilize different assumptions about the nature of the input data and the type of backdoor trigger used in the attack. …”
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Comprehensive Analysis of Word Embedding Models and Design of Effective Feature Vector for Classification of Amazon Product Reviews by B. Priya Kamath, M. Geetha, U. Dinesh Acharya, Dipesh Singh, Ayush Rao, Shwetha Rai, Roopashri Shetty

“…Sentiment Analysis (SA) is a well-known and emerging research field in the area of Natural Language Processing (NLP) and text classification. Feature engineering is considered to be one of the major steps in the Machine Learning (ML) pipeline with effective feature extraction playing a vital role in improving the performance of the SA tasks. …”
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Comparing predictive risk to actual presence of coronary atherosclerosis on coronary computed tomography angiography by Emma Playford, Simon Stewart, Gerard Hoyne, Geoff Strange, Girish Dwivedi, Christian Hamilton-Craig, Gemma Figtree, David Playford

“…Atherosclerosis was extracted using natural language processing of the CCTA report, including the coronary artery calcium score (CACS) and the extent and severity of CAD. …”
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Association of Pneumatosis Intestinalis With Surgical Outcomes and Mortality: A Matched, Retrospective Cohort Study and Literature Review by Kyle D. Klingbeil, MD, MS, Hila Zelicha, PhD, RD, Yijun Chen, MD, Douglas S. Bell, MD, Edward H. Livingston, MD, FACS, AGAF

“…A radiologic diagnosis of PI was then assessed using natural language processing techniques followed by confirmation using manual chart review. …”
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Integrating social narratives of flood events into a text network analysis-based decision support framework to reduce vulnerability to climate change in Africa by Thomas E. O’Shea, Lena C. Grobusch, Mary Zhang, Jeff Neal, Joseph Daron, Richard G. Jones, Christopher Jack, Alice McClure, Gilbert Siame, Dorothy Ndhlovu, Sukaina Bharwani

“…These narratives were used to calibrate the flood maps with insights from Lusaka’s stakeholders using Natural Language Processing (NLP) and Text Network Analysis (TNA). …”
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Explainable Predictive Model for Suicidal Ideation During COVID-19: Social Media Discourse Study by Salah Bouktif, Akib Mohi Ud Din Khanday, Ali Ouni

“…ObjectiveIn this study, our aim was to detect suicidal ideation by mining textual content extracted from social media by leveraging state-of-the-art natural language processing (NLP) techniques. MethodsThe work was divided into 2 major phases, one to classify suicidal ideation posts and the other to extract factors that cause suicidal ideation. …”
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Key Drivers of Consumption, Conceptual, Sensory, and Emotional Profiling of Cheeses Based on Origin and Consumer Familiarity: A Case Study of Local and Imported Cheeses in Greece by Malamatenia Panagiotou, Efstathios Kaloudis, Danai Ioanna Koukoumaki, Vasiliki Bountziouka, Evangelia Giannakou, Margarita Pandi, Konstantinos Gkatzionis

“…Sensory and emotional attributes of local, local PDO, and imported cheeses, as well as drivers associated with consumers’ choice and acceptance above and beyond their sensory attributes, were studied using three methods: (a) flash profile to gain insight into the sensory positioning of products and description of samples; (b) qualitative analysis of focus groups to pinpoint consumer knowledge, preference, and consumption criteria; and (c) a new methodology for natural language processing and sentiment analysis of social media posts to determine consumer conceptualizations. …”
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High clinical burden of classical homocystinuria in the United States: a retrospective analysis by Mahim Jain, Mehul Shah, Kamlesh M. Thakker, Andrew Rava, Agnes Pelts Block, Colette Ndiba-Markey, Lionel Pinto

“…Patients who had 1 or more International Classification of Diseases, Tenth Revision code for homocystinuria (E72.11) or the signs, disease, and symptoms term homocystinuria in the natural language processing dataset were included. To obtain a study population most likely to have HCU, stratifications by tHcy levels, clinical characteristics, and phenotypic expressions were applied to refine the cohort. …”
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Top health service concerns: a data mining study of the Shanghai health hotline by Lili Shi, Tong Zhao, Shimiao Shi, Tianyu Tan, Aksara Regmi, Yuyang Cai

“…We applied natural language processing (NLP) to analyze the content of these work orders, facilitating effective text mining and information extraction. …”
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Artificial intelligence in healthcare: transforming patient safety with intelligent systems—A systematic review by Francesco De Micco, Francesco De Micco, Gianmarco Di Palma, Gianmarco Di Palma, Davide Ferorelli, Anna De Benedictis, Anna De Benedictis, Luca Tomassini, Vittoradolfo Tambone, Mariano Cingolani, Roberto Scendoni, Roberto Scendoni

“…We utilized the online tool Rayyan for efficient screening and selection of relevant studies from three different online bibliographic.ResultsAI systems, including machine learning and natural language processing, show promise in detecting adverse events, predicting medication errors, assessing fall risks, and preventing pressure injuries. …”
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Use of large language models as artificial intelligence tools in academic research and publishing among global clinical researchers by Tanisha Mishra, Edward Sutanto, Rini Rossanti, Nayana Pant, Anum Ashraf, Akshay Raut, Germaine Uwabareze, Ajayi Oluwatomiwa, Bushra Zeeshan

“…Abstract With breakthroughs in Natural Language Processing and Artificial Intelligence (AI), the usage of Large Language Models (LLMs) in academic research has increased tremendously. …”
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ECG-LM: Understanding Electrocardiogram with a Large Language Model by Kai Yang, Massimo Hong, Jiahuan Zhang, Yizhen Luo, Suyuan Zhao, Ou Zhang, Xiaomao Yu, Jiawen Zhou, Liuqing Yang, Ping Zhang, Mu Qiao, Zaiqing Nie

“…Methods: Although recent advancements in multi-modal large language modeling have propelled their application scope beyond the natural language processing domain, their applicability to ECG processing remains largely unexplored, partly due to the lack of text–ECG data. …”
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Understanding Human Papillomavirus Vaccination Hesitancy in Japan Using Social Media: Content Analysis by Junyu Liu, Qian Niu, Momoko Nagai-Tanima, Tomoki Aoyama

“…MethodsWe collected tweets related to the HPV vaccine from 2011 to 2021. Natural language processing techniques and large language models (LLMs) were used for stance analysis of the collected data. …”
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Positional embeddings and zero-shot learning using BERT for molecular-property prediction by Medard Edmund Mswahili, JunHa Hwang, Jagath C. Rajapakse, Kyuri Jo, Young-Seob Jeong

“…The success of transformer-based models, such as the bidirectional encoder representations from transformer (BERT) models, in natural language processing tasks has sparked growing interest from the domain of cheminformatics. …”
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Advancing arabic dialect detection with hybrid stacked transformer models by Hager Saleh, Hager Saleh, Hager Saleh, Abdulaziz AlMohimeed, Rasha Hassan, Mandour M. Ibrahim, Saeed Hamood Alsamhi, Moatamad Refaat Hassan, Sherif Mostafa

“…The rapid expansion of dialectally unique Arabic material on social media and the internet highlights how important it is to categorize dialects accurately to maximize a variety of Natural Language Processing (NLP) applications. The improvement in classification performance highlights the wider variety of linguistic variables that the model can capture, providing a reliable solution for precise Arabic dialect recognition and improving the efficacy of NLP applications. …”
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A phenotype-based AI pipeline outperforms human experts in differentially diagnosing rare diseases using EHRs by Xiaohao Mao, Yu Huang, Ye Jin, Lun Wang, Xuanzhong Chen, Honghong Liu, Xinglin Yang, Haopeng Xu, Xiaodong Luan, Ying Xiao, Siqin Feng, Jiahao Zhu, Xuegong Zhang, Rui Jiang, Shuyang Zhang, Ting Chen

“…PhenoBrain utilizes a BERT-based natural language processing model to extract phenotypes from clinical texts in EHRs and employs five new diagnostic models for differential diagnoses of rare diseases. …”
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