Opportunities and Challenges: The Use of ChatGPT in Enabling Library Knowledge Services by Huaming LI

“…[Purpose/Significance] The generative natural language processing model represented by ChatGPT is beginning to show great application potential in libraries, and its technical advantages coincide with the development needs of knowledge services, greatly improving the quality and efficiency of user services. …”
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Understanding Public Perception of Over‐the‐Counter Hearing Aids: A Sentiment and Thematic Analysis of Consumer Reviews by Joshua W. Cho, Olivia Tandadjaja, Charlie Henriks, Malaika Jamal, Kaitlin Hori, Joel Feier, Ziphron Russel, Ethan Lawrence, Nicole Greene, Janet S. Choi

“…Sentiment analysis was performed using Valence Aware Dictionary and Sentiment Reasoner (VADER), a rule‐based sentiment analysis tool incorporating natural language processing. VADER provides scores for each review ranging from −1 (most negative), 0 (neutral), to 1 (most positive). …”
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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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The Impact of LoRA Adapters on LLMs for Clinical Text Classification Under Computational and Data Constraints by Thanh-Dung Le, Ti Ti Nguyen, Vu Nguyen Ha, Symeon Chatzinotas, Philippe Jouvet, Rita Noumeir

“…Fine-tuning Large Language Models (LLMs) for clinical Natural Language Processing (NLP) poses significant challenges due to domain gap, limited data, and stringent hardware constraints. …”
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The Construction and Application of a Clinical Decision Support System for Cardiovascular Diseases: Multimodal Data-Driven Development and Validation Study by Shumei Miao, Pei Ji, Yongqian Zhu, Haoyu Meng, Mang Jing, Rongrong Sheng, Xiaoliang Zhang, Hailong Ding, Jianjun Guo, Wen Gao, Guanyu Yang, Yun Liu

“…The unstructured data were segmented using natural language processing technology, and medical entity words and entity combination relationships were extracted using IDCNN (iterated dilated convolutional neural network) and TextCNN (text convolutional neural network). …”
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Construction of an AI Literacy General Education Curriculum Based on "Knowledge-Skills" Navigation by Baiyang LI, Rong SUN

“…The foundational cognition level systematically organizes the four key knowledge modules involved in generative artificial intelligence: Machine Learning, Neural Networks, Deep Learning, and Natural Language Processing, helping students to build an initial cognitive framework for GenAI. …”
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Bidirectional Long Short-Term Memory–Based Detection of Adverse Drug Reaction Posts Using Korean Social Networking Services Data: Deep Learning Approaches by Chung-Chun Lee, Seunghee Lee, Mi-Hwa Song, Jong-Yeup Kim, Suehyun Lee

“…Blog posts, café posts, and NAVER Q&A posts from 2005 to 2020 were collected from NAVER, a portal site containing drug-related information, and natural language processing techniques were applied to analyze data written in Korean. …”
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Trans-Border Trusted Data Spaces: A General Framework Supporting Trustworthy International Data Circulation by Chi Zhang, Yan Liu, Mudi Xu, Xingxing Yang, Peng Li, Changshui Yang, Qiang Liu, Xinning Xiong, Pan Chen, Wenyong Wang

“…It also offers multi-party compliance support through a natural language processing (NLP) based rule interpretation framework. …”
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InertDB as a generative AI-expanded resource of biologically inactive small molecules from PubChem by Seungchan An, Yeonjin Lee, Junpyo Gong, Seokyoung Hwang, In Guk Park, Jayhyun Cho, Min Ju Lee, Minkyu Kim, Yun Pyo Kang, Minsoo Noh

“…CIC selection prioritized bioassay diversity, determined using natural language processing (NLP)-based clustering metrics, while ensuring minimal biological activity across all evaluated bioassays. …”
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TECRR: a benchmark dataset of radiological reports for BI-RADS classification with machine learning, deep learning, and large language model baselines by Sadam Hussain, Usman Naseem, Mansoor Ali, Daly Betzabeth Avendaño Avalos, Servando Cardona-Huerta, Beatriz Alejandra Bosques Palomo, Jose Gerardo Tamez-Peña

“…Abstract Background Recently, machine learning (ML), deep learning (DL), and natural language processing (NLP) have provided promising results in the free-form radiological reports’ classification in the respective medical domain. …”
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BlueEdge: application design for big data cleaning processing using mobile edge computing environments by Nagwa Elmobark, Haitham El-ghareeb, Sara Elhishi

“…BlueEdge utilizes Natural Language Processing (NLP) techniques, including those from the Natural Language Toolkit (NLTK) and Python packages, to connect with a real-time database. …”
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Evaluating the performance of artificial intelligence-based speech recognition for clinical documentation: a systematic review by Joel Jia Wei Ng, Eugene Wang, Xinyan Zhou, Kevin Xiang Zhou, Charlene Xing Le Goh, Gabriel Zheng Ning Sim, Hiang Khoon Tan, Serene Si Ning Goh, Qin Xiang Ng

“…AI-driven transcription systems utilizing automatic speech recognition (ASR) and natural language processing (NLP) aim to automate and enhance the accuracy and efficiency of clinical documentation. …”
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Assessing the Efficiency of Transformer Models with Varying Sizes for Text Classification: A Study of Rule-Based Annotation with DistilBERT and Other Transformers by Arafet Sbei, Khaoula ElBedoui, Walid Barhoumi

“…The proposed hybrid method offers a robust and adaptable solution for sentence annotation pipelines, enhancing performance in diverse natural language processing applications with limited labeled data. …”
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Osteosarcoma knowledge graph question answering system: deep learning-based knowledge graph and large language model fusion by Lulu Zhang, Weisong Zhao, Zhiwei Cheng, Yafei Jiang, Kai Tian, Jia Shi, Zhenyu Jiang, Yingqi Hua

“…This system employs advanced natural language processing and incorporates the OSKG to ensure optimal response quality and accuracy. …”
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Evaluating Medical Entity Recognition in Health Care: Entity Model Quantitative Study by Shengyu Liu, Anran Wang, Xiaolei Xiu, Ming Zhong, Sizhu Wu

“…MethodsThis study comprehensively evaluated 7 NER models—hidden Markov models, conditional random fields, BERT for Biomedical Text Mining, Big Transformer Models for Efficient Long-Sequence Attention, Decoding-enhanced BERT with Disentangled Attention, Robustly Optimized BERT Pretraining Approach, and Gemma—across 3 medical datasets: Revised Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA), BioCreative V CDR, and Anatomical Entity Mention (AnatEM). …”
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Research trends among new investigators at ISOQOL: a bibliometric analysis from 2019 to 2023 by Jae-Yung Kwon, Manraj N. Kaur, Ellen B. M. Elsman, Ava Mehdipour, Lori Suet Hang Lo, Ahmed M. Y. Osman, Sandrine Herbelet, Carrie-Anne Ng, Lotte van der Weijst, on behalf of the New Investigators Special Interest Group Members

“…Expanding partnerships with underrepresented regions and embracing advanced technologies such as natural language processing could foster inclusivity and drive transformative advancements in QoL measurement and application.…”
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Generating Parathyroid Reports Using YOLO-Based Large Language Models by Chuan-Yu Chang, Abida Khanum, Chiao-Yin Sun, Ying-Ting Chen, Yu-Chen Tsai, Chih-Chin Hsu

“…Combining image-based diagnostic insights with advanced natural language processing minimizes errors caused by human factors such as inexperience or fatigue, offering robust support for radiologists. …”
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Effect of an algorithm for automatic placing of standardised test order sets on low-value appointments and attendance rates at four Spanish teaching hospitals: an interrupted time... by Emilio Calvo, Juan Antonio Álvaro de la Parra, Marta del Olmo Rodríguez, Cristina Caramés Sánchez, Ángel Blanco, Bernadette Pfang, Sagrario Mayoralas-Alises, Jose Fernandez-Ferro, Óscar Gómez Martín, Jesús Fernández Tabera, Carmen Plaza Nohales, Carlota Nieto, Jorge Short Apellaniz

“…We conducted an interrupted time series analysis demonstrating the effect of an algorithm for placing automatic test order sets prior to first specialist appointment on avoidable follow-up appointments and attendance rates.Design Interrupted time series analysis.Setting 4 academic hospitals from Madrid, Spain.Participants Patients referred from primary care attending 10 033 470 outpatient appointments from 16 clinical specialties during a 6-year period (1 January 2018 to 30 June 2023).Intervention An algorithm using natural language processing was launched in May 2021. Test order sets developed for 257 presenting complaints from 16 clinical specialties were placed automatically before first specialist appointments to increase rates of diagnosis and initiation of treatment with discharge back to primary care.Primary and secondary outcome measures Primary outcomes included rate of diagnosis and discharge to primary care and follow-up to first appointment index. …”
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Syntactic complexity recognition and analysis in Chinese-English machine translation: A comparative study based on the BLSTM-CRF model. by Yongli Tian

“…This study offers new insights into syntactic complexity modeling in natural language processing and provides valuable theoretical and practical contributions to syntactic processing in machine translation systems.…”
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What is the Role of Medical Informatics in Digital Healthcare? by Mihai TĂRÂŢĂ

“… • AI & Automation in Medical Workflows – Utilizing NLP (Natural Language Processing) to extract insights from medical literature and clinical notes while automating administrative processes such as billing and scheduling…”
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