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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Perbandingan Pretrained Model Transformer pada Deteksi Ulasan Palsu by Aisyah Awalina, Fitra Abdurrachman Bachtiar, Fitri Utaminingrum

“…Transformer models are currently widely applied to natural language processing because they have outstanding performance. …”
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The Impact of Artificial Intelligence on Healthcare: A Comprehensive Review of Advancements in Diagnostics, Treatment, and Operational Efficiency by Md. Faiyazuddin, Syed Jalal Q. Rahman, Gaurav Anand, Reyaz Kausar Siddiqui, Rachana Mehta, Mahalaqua Nazli Khatib, Shilpa Gaidhane, Quazi Syed Zahiruddin, Arif Hussain, Ranjit Sah

“…The study aims to describe AI in healthcare, including important technologies like robotics, machine learning (ML), deep learning (DL), and natural language processing (NLP), and to investigate how these technologies are used in patient interaction, predictive analytics, and remote monitoring. …”
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Advancing health equity: evaluating AI translations of kidney donor information for Spanish speakers by Oscar A. Garcia Valencia, Charat Thongprayoon, Caroline C. Jadlowiec, Shennen A. Mao, Napat Leeaphorn, Pooja Budhiraja, Nadeen Khoury, Justin H. Pham, Iasmina M. Craici, Maria L. Gonzalez Suarez, Wisit Cheungpasitporn

“…ChatGPT, an AI language model with sophisticated natural language processing capabilities, has been identified as a promising tool for translating critical health information into Spanish. …”
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Analisis Perbandingan Model Bert Dan Xlnet Untuk Klasifikasi Tweet Bully Pada Twitter by Teuku Radillah, Okta Veza, Sarjon Defit

“…This study aims to compare the performance of two recent natural language processing models, namely BERT (Bidirectional Encoder Representations from Transformers) and XLNet, in the classification of tweets containing bullying. …”
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The role of artificial intelligence and machine learning in predicting and combating antimicrobial resistance by Hazrat Bilal, Muhammad Nadeem Khan, Sabir Khan, Muhammad Shafiq, Wenjie Fang, Rahat Ullah Khan, Mujeeb Ur Rahman, Xiaohui Li, Qiao-Li Lv, Bin Xu

“…Supervised learning, unsupervised learning, deep learning, reinforcement learning, and natural language processing are some of the main tools used in this domain. …”
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Association of delayed asthma diagnosis with asthma exacerbations in children by Chung-Il Wi, MD, Euijung Ryu, PhD, Katherine S. King, MS, Jung Hyun Kwon, MD, PhD, Joshua T. Bublitz, BS, Miguel Park, MD, Sergio E. Chiarella, MD, Jason D. Greenwood, MD, MS, Thanai Pongdee, MD, Lynnea Myers, PhD, Björn Nordlund, PhD, Sunghwan Sohn, PhD, Elham Sagheb, MS, Bhavani Singh Agnikula Kshatriya, MS, Dave Watson, PhD, Hongfang Liu, PhD, Beverley J. Sheares, MD, MS, Carla M. Davis, MD, Wade Schulz, MD, PhD, Young J. Juhn, MD, MPH

“…We defined onset date as the date when subjects first met predetermined asthma criteria ascertained by an electronic health records–based natural language processing algorithm. Delay in diagnosis (DD) was defined as first diagnosis >30 days from onset date (vs timely diagnosis [TD] within 30 days). …”
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NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation by Kaustubh Dhole, Varun Gangal, Sebastian Gehrmann, Aadesh Gupta, Zhenhao Li, Saad Mahamood, Abinaya Mahadiran, Simon Mille, Ashish Shrivastava, Samson Tan, Tongshang Wu, Jascha Sohl-Dickstein, Jinho Choi, Eduard Hovy, Ondřej Dušek, Sebastian Ruder, Sajant Anand, Nagender Aneja, Rabin Banjade, Lisa Barthe, Hanna Behnke, Ian Berlot-Attwell, Connor Boyle, Caroline Brun, Marco Antonio Sobrevilla Cabezudo, Samuel Cahyawijaya, Emile Chapuis, Wanxiang Che, Mukund Choudhary, Christian Clauss, Pierre Colombo, Filip Cornell, Gautier Dagan, Mayukh Das, Tanay Dixit, Thomas Dopierre, Paul-Alexis Dray, Suchitra Dubey, Tatiana Ekeinhor, Marco Di Giovanni, Tanya Goyal, Rishabh Gupta, Louanes Hamla, Sang Han, Fabrice Harel-Canada, Antoine Honoré, Ishan Jindal, Przemysław Joniak, Denis Kleyko, Venelin Kovatchev, Kalpesh Krishna, Ashutosh Kumar, Stefan Langer, Seungjae Ryan Lee, Corey James Levinson, Hualou Liang, Kaizhao Liang, Zhexiong Liu, Andrey Lukyanenko, Vukosi Marivate, Gerard de Melo, Simon Meoni, Maxine Meyer, Afnan Mir, Nafise Sadat Moosavi, Niklas Meunnighoff, Timothy Sum Hon Mun, Kenton Murray, Marcin Namysl, Maria Obedkova, Priti Oli, Nivranshu Pasricha, Jan Pfister, Richard Plant, Vinay Prabhu, Vasile Pais, Libo Qin, Shahab Raji, Pawan Kumar Rajpoot, Vikas Raunak, Roy Rinberg, Nicholas Roberts, Juan Diego Rodriguez, Claude Roux, Vasconcellos Samus, Ananya Sai, Robin Schmidt, Thomas Scialom, Tshephisho Sefara, Saqib Shamsi, Xudong Shen, Yiwen Shi, Haoyue Shi, Anna Shvets, Nick Siegel, Damien Sileo, Jamie Simon, Chandan Singh, Roman Sitelew, Priyank Soni, Taylor Sorensen, William Soto, Aman Srivastava, Aditya Srivatsa, Tony Sun, Mukund Varma, A Tabassum, Fiona Tan, Ryan Teehan, Mo Tiwari, Marie Tolkiehn, Athena Wang, Zijian Wang, Zijie Wang, Gloria Wang, Fuxuan Wei, Bryan Wilie, Genta Indra Winata, Xinyu Wu, Witold Wydmanski, Tianbao Xie, Usama Yaseen, Michael Yee, Jing Zhang, Yue Zhang

“… Data augmentation is an important method for evaluating the robustness of and enhancing the diversity of training data for natural language processing (NLP) models. In this paper, we present NL-Augmenter, a new participatory Python-based natural language (NL) augmentation framework which supports the creation of transformations (modifications to the data) and filters (data splits according to specific features). …”
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Navigating Ethical Dilemmas Of Generative AI In Medical Writing by Qurrat Ulain Hamdan, Waleed Umar, Mahnoor Hasan

“…Generative AI in Medical Writing Generative AI tools or “chatbots” combine the adaptive learning capabilities of deep learning algorithms and natural language processing, resulting in a virtual assistant or aide that is capable of answering queries, following commands, and improving its responses according to the vast data available on the Internet in addition to user responses.3 This has allowed the accomplishment of various complex tasks within seconds that would otherwise require hours of trial and error. …”
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Association of glycemic control with Long COVID in patients with type 2 diabetes: findings from the National COVID Cohort Collaborative (N3C) by Jane E B Reusch, Rachel Wong, Nasia Safdar, Harold Lehmann, Brijesh Patel, Til Stürmer, Hongfang Liu, Peter Robinson, Elaine Hill, Richard Moffitt, Justin Guinney, Joel Gagnier, Cavin Ward-Caviness, Noha Sharafeldin, Justin Starren, Amit Saha, Lesley Cottrell, Melissa A Haendel, Margaret A Hall, Vignesh Subbian, Kristin Kostka, Farrukh M Koraishy, Andrew E Williams, Robert Hurley, Steve Johnson, Usman Sheikh, Rishi Kamaleswaran, Christopher Dillon, Michele Morris, Randeep Jawa, Hemalkumar Mehta, Benjamin Bates, Tellen D Bennett, Nabeel Qureshi, Katie Rebecca Bradwell, Federico Mariona, Adam B Wilcox, Adam M Lee, Alexis Graves, Amin Manna, Amy Olex, Andrea Zhou, Andrew Southerland, Andrew T Girvin, Anita Walden, Anjali A Sharathkumar, Benjamin Amor, Brian Hendricks, Caleb Alexander, Carolyn Bramante, Charisse Madlock-Brown, Christine Suver, Christopher Chute, Chunlei Wu, Clare Schmitt, Cliff Takemoto, Dan Housman, Davera Gabriel, David A Eichmann, Diego Mazzotti, Eilis Boudreau Don Brown, Elizabeth Zampino, Emily Carlson Marti, Emily R Pfaff, Evan French, Fred Prior, George Sokos, Greg Martin, Heidi Spratt, Hythem Sidky, JW Awori Hayanga, Jami Pincavitch, Jaylyn Clark, Jeremy Richard Harper, Jessica Islam, Jin Ge, Joel H Saltz, Joel Saltz, Johanna Loomba, John Buse, Jomol Mathew, Joni L Rutter, Julie A McMurry, Karen Crowley, Kellie M Walters, Ken Wilkins, Kenneth R Gersing, Kenrick Dwain Cato, Kimberly Murray, Lavance Northington, Lee Allan Pyles, Leonie Misquitta, Lili Portilla, Mariam Deacy, Mark M Bissell, Marshall Clark, Mary Emmett, Mary Morrison Saltz, Matvey B Palchuk, Meredith Adams, Meredith Temple-O'Connor, Michael G Kurilla, Nicole Garbarini, Ofer Sadan, Patricia A Francis, Penny Wung Burgoon, Rafael Fuentes, Rebecca Erwin-Cohen, Richard A Moffitt, Richard L Zhu, Robert T Miller, Saiju Pyarajan, Sam G Michael, Samuel Bozzette, Sandeep Mallipattu, Satyanarayana Vedula, Scott Chapman, T Shawn, Soko Setoguchi O'Neil, Stephanie S Hong, Tiffany Callahan, Umit Topaloglu, Valery Gordon, Warren A Kibbe, Wenndy Hernandez, Will Beasley, Will Cooper, William Hillegass, Xiaohan Tanner Zhang, Samuel Soff, Yun Jae Yoo, Jared Davis Huling, Daniel Brannock, Zachary Butzin-Dozier, Alfred Jerrod Anzalone, Philip RO. Payne, Rena Patel

“…Our cohort included individuals with T2D from eight sites with longitudinal natural language processing (NLP) data. The primary outcome was death or new-onset recurrent Long COVID symptoms within 30–180 days after COVID-19. …”
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A Novel Approach to Word Sense Disambiguation Based on Topical and Semantic Association by Xin Wang, Wanli Zuo, Ying Wang

“…Word sense disambiguation (WSD) is a fundamental problem in nature language processing, the objective of which is to identify the most proper sense for an ambiguous word in a given context. …”
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Deep Recurrent Model for Server Load and Performance Prediction in Data Center by Zheng Huang, Jiajun Peng, Huijuan Lian, Jie Guo, Weidong Qiu

“…Recurrent neural network (RNN) has been widely applied to many sequential tagging tasks such as natural language process (NLP) and time series analysis, and it has been proved that RNN works well in those areas. …”
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