Integrating machine learning and sentiment analysis in movie recommendation systems by Amany M. Sarhan, Hager Ayman, Mariam Wagdi, Bassant Ali, Aliaa Adel, Rahf Osama

“…Sentiment-based movie recommendation system research employs techniques such as natural language processing and hybrid models with the goal of increasing user satisfaction. …”
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Changes in recreational drug use, reasons for those changes and their consequence during and after the COVID-19 pandemic in the UK by Maria Bălăeţ, Ana Zadel, Anne Lingford-Hughes, Louise M. Paterson, Samuel R. Chamberlain, William Trender, Peter J. Hellyer, Adam Hampshire

“…We employed natural language processing and machine learning to analyse a large dataset of self-reported rates of and reasons for drug use during the pandemic, along with their associations with anxiety, depression and substance use problems post-pandemic. …”
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A protocol for three observational cohort studies evaluating adverse outcomes, excess costs and repeat procedures after surgery for breast cancer in the USA by Sam E Wing, Yuki Liu, Jonathan C Johnson, Kristin J Moore, Feibi Zheng

“…Patients will be included based on specific procedure and diagnosis codes, with additional data extracted from unstructured clinical notes using natural language processing. The study will analyze patient demographics, baseline health, surgical details, and outcomes, including costs, complications, reoperations and mortality. …”

Distinguishing clinical and genetic risk factors for suicidal ideation and behavior in a diverse hospital population by Sarah M. C. Colbert, Lauren Lepow, Brian Fennessy, Nakao Iwata, Masashi Ikeda, Takeo Saito, Chikashi Terao, Michael Preuss, Jyotishman Pathak, J. John Mann, Hilary Coon, Niamh Mullins

“…We used ICD codes and a natural language processing algorithm to identify individuals in a hospital biobank with SI-only, SB, and controls without either. …”
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Assessing cross cultural urban park emotional wellbeing impact in Shanghai and London by Zijuan Zhao, Qingying He, Yaqiong Zhang, Sidi liu, Ying Yang

“…We collected text data from Weibo and Twitter, applying natural language processing techniques to quantify emotion scores. …”
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Video Temporal Grounding with Multi-Model Collaborative Learning by Yun Tian, Xiaobo Guo, Jinsong Wang, Bin Li, Shoujun Zhou

“…Functioning as a critical conduit between computer vision and natural language processing, this task holds profound importance in advancing video comprehension. …”
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Supervised learning and resampling techniques on DISC personality classification using Twitter information in Bahasa Indonesia by Ema Utami, Irwan Oyong, Suwanto Raharjo, Anggit Dwi Hartanto, Sumarni Adi

“…A pure natural language processing (NLP) approach can give decent results, and its reliability can be improved by combining it with machine learning (as shown by previous studies). …”
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ChatGPT versus human in generating medical graduate exam multiple choice questions-A multinational prospective study (Hong Kong S.A.R., Singapore, Ireland, and the United Kingdom). by Billy Ho Hung Cheung, Gary Kui Kai Lau, Gordon Tin Chun Wong, Elaine Yuen Phin Lee, Dhananjay Kulkarni, Choon Sheong Seow, Ruby Wong, Michael Tiong-Hong Co

“…<h4>Introduction</h4>Large language models, in particular ChatGPT, have showcased remarkable language processing capabilities. Given the substantial workload of university medical staff, this study aims to assess the quality of multiple-choice questions (MCQs) produced by ChatGPT for use in graduate medical examinations, compared to questions written by university professoriate staffs based on standard medical textbooks.…”
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Multilingual identification of nuanced dimensions of hope speech in social media texts by Grigori Sidorov, Fazlourrahman Balouchzahi, Luis Ramos, Helena Gómez-Adorno, Alexander Gelbukh

“…Abstract Hope plays a crucial role in human psychology and well-being, yet its expression and detection across languages remain underexplored in natural language processing (NLP). This study presents MIND-HOPE, the first-ever multiclass hope speech detection datasets for Spanish and German, collected from Twitter. …”
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Improving drug-drug interaction prediction via in-context learning and judging with large language models by He Qi, He Qi, Xiaoqiang Li, Chengcheng Zhang, Tianyi Zhao, Tianyi Zhao

“…IntroductionLarge Language Models (LLMs), recognized for their advanced capabilities in natural language processing, have been successfully employed across various domains. …”
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Autocorrelation Matrix Knowledge Distillation: A Task-Specific Distillation Method for BERT Models by Kai Zhang, Jinqiu Li, Bingqian Wang, Haoran Meng

“…Pre-trained language models perform well in various natural language processing tasks. However, their large number of parameters poses significant challenges for edge devices with limited resources, greatly limiting their application in practical deployment. …”
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IMViT: Adjacency Matrix-Based Lightweight Plain Vision Transformer by Qihao Chen, Yunfeng Yan, Xianbo Wang, Jishen Peng

“…Transformers are becoming dominant deep learning backbones for both computer vision and natural language processing. While extensive experiments prove its outstanding ability for large models, transformers with small sizes are not comparable with convolutional neural networks in various downstream tasks due to its lack of inductive bias which can benefit image understanding. …”
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Using transformers and Bi-LSTM with sentence embeddings for prediction of openness human personality trait by Anam Naz, Hikmat Ullah Khan, Tariq Alsahfi, Mousa Alhajlah, Bader Alshemaimri, Ali Daud

“…In this research work, we aim to explore diverse natural language processing (NLP) based features and apply state of the art deep learning algorithms for openness trait prediction. …”
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Survey and Evaluation of Converging Architecture in LLMs Based on Footsteps of Operations by Seongho Kim, Jihyun Moon, Juntaek Oh, Insu Choi, Joon-Sung Yang

“…Large language models (LLMs), which have emerged from advances in natural language processing (NLP), enable chatbots, virtual assistants, and numerous domain-specific applications. …”
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A Scoping Review to Identify Community- and Societal-Level Strategies Evaluated from 2013 to 2023 for Their Potential Impact on Child Well-Being in the United States by Katie A. Ports, Whitney L. Rostad, Peter Coyne, Jadyn Dunning, Andrea E. Gonzalez, Adam Troy

“…A total of 29,079 records were identified using natural language processing with 341 records meeting inclusion criteria (e.g., outcomes focused on child well-being, interventions happening at a population level, and evaluations of prevention strategies in the United States). …”
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Multi-Domain Controversial Text Detection Based on a Machine Learning and Deep Learning Stacked Ensemble by Jiadi Liu, Zhuodong Liu, Qiaoqi Li, Weihao Kong, Xiangyu Li

“…Due to the rapid proliferation of social media and online reviews, the accurate identification and classification of controversial texts has emerged as a significant challenge in the field of natural language processing. However, traditional text-classification methodologies frequently encounter critical limitations, such as feature sensitivity and inadequate generalization capabilities. …”
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Research on adverse event classification algorithm of da Vinci surgical robot based on Bert-BiLSTM model by Tianchun Li, Wanting Zhu, Wenke Xia, Li Wang, Weiqi Li, Peiming Zhang

“…This study aims to enhance the classification accuracy of adverse events associated with the da Vinci surgical robot through advanced natural language processing techniques, thereby ensuring medical device safety and protecting patient health. …”
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Distribution of trial registry numbers within full-text of PubMed Central articles: implications for linking trials to publications and indexing trial publication types by Arthur M. Holt, Ang Michael Troy, Neil R. Smalheiser

“…A variety of natural language processing (NLP)-based and machine learning-based models have been developed to assist users in identifying these connections. …”
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Explainable educational assistant integrated in Moodle: automated semantic assessment and adaptive tutoring based on NLP and XAI by William Villegas-Ch, Rommel Gutierrez, Joselin García-Ortiz, Vanessa Guevara

“…In response to this gap, we developed and validated an explainable natural language processing (NLP)-based educational assistant that integrates semantic analysis, justification of evaluations, and adaptive tutoring into a unified, modular architecture embedded in Moodle. …”
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Detection of Malicious Office Open Documents (OOXML) Using Large Language Models: A Static Analysis Approach by Jonas Heß , Kalman Graffi

“…The method involves extracting textual content from Office documents and utilising advanced natural language processing techniques provided by LLMs to analyse the documents for potentially malicious indicators. …”
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