Assessing and Scoring Difficulty of Hard-to-Solve Data in Summarization Tasks by Jeesu Jung, Hyein Seo, Hyuk Namgoong, Sangkeun Jung

“…In recent years, data-driven and machine learning-based natural language processing (NLP) technologies have effectively addressed various challenges. …”
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A review of university chatbots for student support: FAQs and beyond by Kevin Peyton, Saritha Unnikrishnan, Brian Mulligan

“…It initially describes chatbot examples related to student administration activities and teaching and learning, before describing in detail the recent evolution of Natural Language Processing and the more immediate arrival of state-of-the-art generative techniques. …”
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Needle in a haystack: Harnessing AI in drug patent searches and prediction. by Leonardo Costa Ribeiro, Valbona Muzaka

“…Taking advantage of advances in artificial intelligence and in natural language processing in particular, we offer a new method of identifying chemical drug-related patents in this article. …”
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From discovery to delivery: Governance of AI in the pharmaceutical industry by Stephanie Pasas-Farmer, Rashi Jain

“…Key AI technologies like machine learning, deep learning, natural language processing, and computer vision are transforming pharmaceutical practices. …”
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Addressing grading bias in rock climbing: machine and deep learning approaches by B. O’Mara, M. S. Mahmud

“…Of these, the most optimal methods used natural language processing or recurrent neural network algorithms. …”
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Hydrogen-Powered Aviation: Insights from a Cross-Sectional Scientometric and Thematic Analysis of Patent Claims by Raj Bridgelall

“…Thematic word clouds and term co-occurrence networks based on natural language processing techniques validate these classifications and highlight core technical themes. …”
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Creating a diagnostic assessment model for autism spectrum disorder by differentiating lexicogrammatical choices through machine learning. by Sumi Kato, Kazuaki Hanawa, Manabu Saito, Kazuhiko Nakamura

“…This approach suggests the possibility of using natural language processing to detect distinctive linguistic patterns in AS, aiming to enhance diagnostic accuracy for differentiating AS from non-AS in adolescents and adults.…”
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Visual explainable artificial intelligence for graph-based visual question answering and scene graph curation by Sebastian Künzel, Tanja Munz-Körner, Pascal Tilli, Noel Schäfer, Sandeep Vidyapu, Ngoc Thang Vu, Daniel Weiskopf

“…The authors evaluated their tool through the demonstration of identified use cases, quantitative measures, and a user study conducted with experts from machine learning, visualization, and natural language processing domains. The authors’ findings highlight the prominence of their implemented features in supporting the users with incorrect prediction identification and identifying the underlying issues. …”
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Artificial intelligence in aviation English testing by Gökhan Demirdöken

“…The review encompasses AI technologies such as automated speech recognition (ASR), natural language processing (NLP), and intelligent tutoring systems (ITS) in the light of the language proficiency requirements stated by the International Civil Aviation Organization (ICAO). …”
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Application and Development of Large Language Models in Smart Inhalers by Wenxu Guo, Zhihong Cheng, Jian Wang

“…LLMs can optimize the functionality of smart inhalers, enhance patient education and feedback mechanisms, and support personalized medical decision-making through natural language processing and deep data analysis. However, the application of these technologies also presents numerous challenges. …”
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AI Agents and the Dawn of Post-Authenticity by Octavian Dumitru HERA

“…It explores advancements in natural language processing and image recognition, which allow for the creation of highly convincing fake content. …”
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Detecting the Presence of Named Entities in Bengali: Corpus and Experiments by Farzana Rashid, Fahmida Hamid

“…Named Entity Recognition (NER) belongs to the field of Information Extraction (IE) and Natural Language Processing (NLP). NER aims to find and categorize named entities present in the textual data into recognizable classes. …”
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Language models outperform cloze predictability in a cognitive model of reading. by Adrielli Tina Lopes Rego, Joshua Snell, Martijn Meeter

“…This is the first study to use LLMs to augment a cognitive model of reading with higher-order language processing while proposing a mechanism on the interplay between word predictability and eye movements.…”
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Traffic concealed data detection method based on contrastive learning and pre-trained Transformer by HE Shuai, ZHANG Jingchao, XU Di, JIANG Shuai, GUO Xiaowei, FU Cai

“…Considering the high complexity, unstructured nature of encrypted traffic, and the insufficient performance of traditional fine-tuning methods for downstream tasks in the encrypted traffic domain, data packets were first transformed into tokens which was similar to those used in natural language processing. Then, a pre-trained Transformer model was utilized to convert shallow representations into a general traffic representation, which was suitable for various encrypted traffic downstream tasks. …”
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Lazy Network: A Word Embedding-Based Temporal Financial Network to Avoid Economic Shocks in Asset Pricing Models by George Adosoglou, Seonho Park, Gianfranco Lombardo, Stefano Cagnoni, Panos M. Pardalos

“…In this study, we combine natural language processing techniques and network science to introduce a novel 10-K-based network, named Lazy Network, that leverages year-on-year changes in companies’ 10-Ks detected using a neural network embedding model. …”
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Automated sample annotation for diabetes mellitus in healthcare integrated biobanking by Johannes Stolp, Christoph Weber, Danny Ammon, André Scherag, Claudia Fischer, Christof Kloos, Gunter Wolf, P. Christian Schulze, Utz Settmacher, Michael Bauer, Andreas Stallmach, Michael Kiehntopf, Boris Betz

“…The study evaluates a machine learning (ML) and natural language processing (NLP) based two-step procedure for timely and precise sample annotation for diabetes mellitus. …”
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The Association of Aortic Stenosis Severity and Symptom Status With Morbidity and Mortality by Matthew D. Solomon, MD, PhD, Alan S. Go, MD, Thomas Leong, MPH, Elisha Garcia, BS, Kathy Le, MPH, Femi Philip, MD, Edward McNulty, MD, Jacob Mishell, MD, Andrew N. Rassi, MD, David C. Lange, MD, Catherine Lee, PhD, Anthony DeMaria, MD, Rick Nishimura, MD, Andrew P. Ambrosy, MD

“…Methods: In this retrospective cohort study from a large, integrated health care system serving >4.5 M individuals, we applied validated natural language processing algorithms to echocardiogram reports to identify physician-assessed AS severity and potential AS-related symptoms (eg, chest pain, syncope, dyspnea, worsening heart failure) via diagnosis codes and natural language processing-applied physician notes. …”
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Evidence of functional connectivity disruptions between auditory and non-auditory regions in adolescents living with HIV by Joanah Madzime, Joanah Madzime, Marcin Jankiewicz, Marcin Jankiewicz, Marcin Jankiewicz, Ernesta M. Meintjes, Ernesta M. Meintjes, Ernesta M. Meintjes, Peter Torre, Barbara Laughton, Martha J. Holmes, Martha J. Holmes, Martha J. Holmes, Martha J. Holmes

“…IntroductionChildren living with perinatally acquired HIV (CPHIV) demonstrate hearing impairments and language processing delays even in the presence of combination antiretroviral therapy (cART). …”
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Impact of Respectfulness on Semantic Integration During Discourse Processing by Wenjing Yu, Yuhan Xie, Xiaohong Yang

“…Previous studies have shown respectful term usage affects online language processing. This study investigates its impact on semantic integration through three self-pace reading experiments, manipulating Respect Consistency (Respect vs. …”
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An NLP-based method to mine gene and function relationships from published articles by Nilesh Kumar, M. Shahid Mukhtar

“…We introduce PATHAK, a natural language processing (NLP)-based method that mines relationships between genes and their functions from published scientific articles. …”
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