Prediction of inhibitory peptides against E.coli with desired MIC value by Nisha Bajiya, Nishant Kumar, Gajendra P. S. Raghava

“…Subsequently, we employed machine learning regression models that integrated various features, including peptide composition, binary profiles and embeddings from large language models. Feature selection techniques, particularly mRMR, were utilized to refine our model inputs. …”
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Era of Generalist Conversational Artificial Intelligence to Support Public Health Communications by Emre Sezgin, Ahmet Baki Kocaballi

“…Specifically, we discuss the integration of large language models and generative AI in mainstream messaging platforms, which potentially outperform traditional information retrieval systems in public health contexts. …”
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Me vs. the machine? Subjective evaluations of human- and AI-generated advice by Merrick R. Osborne, Erica R. Bailey

“…In addition, we shift the focus in a new direction—exploring how interacting with AI tools, specifically large language models, impacts the user’s view of themselves. …”
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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

“…In a human-computer study with 75 cases, PhenoBrain exhibited exceptional performance with a top-3 recall of 0.613 and a top-10 recall of 0.813, surpassing the performance of 50 specialist physicians and large language models like ChatGPT and GPT-4. Combining PhenoBrain’s predictions with specialists increased the top-3 recall to 0.768, demonstrating its potential to enhance diagnostic accuracy in clinical workflows.…”
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Enhancing zero-shot stance detection via multi-task fine-tuning with debate data and knowledge augmentation by Qinlong Fan, Jicang Lu, Yepeng Sun, Qiankun Pi, Shouxin Shang

“…To address these challenges, we propose combining fine-tuning of Large Language Models (LLMs) with knowledge augmentation for zero-shot stance detection. …”
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Quantum theory-inspired inter-sentence semantic interaction model for textual adversarial defense by Jiacheng Huang, Long Chen, Xiaoyin Yi, Ning Yu

“…Comprehensive experiments are conducted to validate the efficacy of proposed methodology, and the results underscore its superiority over baseline models even commercial applications based on large language models in terms of accuracy across diverse adversarial attack scenarios, showing the potential of proposed approach in enhancing the robustness of neural networks under adversarial attacks.…”
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Signals of propaganda-Detecting and estimating political influences in information spread in social networks. by Alon Sela, Omer Neter, Václav Lohr, Petr Cihelka, Fan Wang, Moti Zwilling, John Phillip Sabou, Miloš Ulman

“…Furthermore, with the recent exponential growth in large language models (L.L.M), and the growing concerns about information overload, which makes the alternative truth spheres more noisy than ever before, the complexity and magnitude of computational propaganda is also expected to increase, making their detection even harder. …”
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A Review of CNN Applications in Smart Agriculture Using Multimodal Data by Mohammad El Sakka, Mihai Ivanovici, Lotfi Chaari, Josiane Mothe

“…Future directions point toward integrating IoT and cloud platforms for real-time data processing and leveraging large language models for regulatory insights. Potential research advancements emphasize improving increased data accessibility and hybrid modeling to meet the agricultural demands of climate variability and food security, positioning CNNs as pivotal tools in sustainable agricultural practices. …”
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GenSQLi: A Generative Artificial Intelligence Framework for Automatically Securing Web Application Firewalls Against Structured Query Language Injection Attacks by Vahid Babaey, Arun Ravindran

“…This paper introduces a novel generative AI framework designed to enhance SQLi mitigation by leveraging Large Language Models (LLMs). The framework achieves two primary objectives: (1) generating diverse and validated SQLi payloads using in-context learning, thereby minimizing hallucinations, and (2) automating defense mechanisms by testing these payloads against a vulnerable web application secured by a WAF, classifying bypassing attacks, and constructing effective WAF security rules through generative AI techniques. …”
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Sequence Analysis-Enhanced AI: Transforming Interactive E-Book Data into Educational Insights for Teachers by Yaroslav Opanasenko, Emanuele Bardone, Margus Pedaste, Leo Aleksander Siiman

“…This study explores the potential of large language models as interfaces for conducting sequence analysis on log data from interactive E-Books. …”
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Urdu Toxic Comment Classification With PURUTT Corpus Development by Hafiz Hassaan Saeed, Tahir Khalil, Faisal Kamiran

“…Furthermore, we fine-tune five multilingual large language models capitalizing on their inherent multilingual capabilities. …”
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Machine Reading Comprehension for the Tamil Language With Translated SQuAD by Anton Vijeevaraj Ann Sinthusha, Eugene Y. A. Charles, Ruvan Weerasinghe

“…However, MRC for low-resourced languages (LRL) remains an ongoing research area. Although Large Language Models show exceptional NLP performance, they are less effective for LRL and are expensive to train and deploy. …”
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From deliberation to acclamation: how did Twitter’s algorithms foster polarized communities and undermine democracy in the 2020 US presidential election by Gustavo Morales, Gustavo Morales, Augusto Salazar, Diego Puche

“…To develop a comprehensive analysis of large interaction datasets, we propose a novel methodology leveraging large language models to automate the classification process. …”
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An Innovative Solution to Design Problems: Applying the Chain-of-Thought Technique to Integrate LLM-Based Agents With Concept Generation Methods by Shijun Ge, Yuanbo Sun, Yin Cui, Dapeng Wei

“…To enhance the application capabilities of large language models (LLMs) in conceptual design, this study explores how to achieve deep integration between LLM-based agents and concept generation methods using the chain-of-thought (CoT) technique and evaluates its feasibility. …”
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The Role of ChatGPT and AI Chatbots in Optimizing Antibiotic Therapy: A Comprehensive Narrative Review by Ninel Iacobus Antonie, Gina Gheorghe, Vlad Alexandru Ionescu, Loredana-Crista Tiucă, Camelia Cristina Diaconu

“…Artificial intelligence (AI) chatbots based on large language models have shown potential as tools to support clinicians, especially non-specialists, in optimizing antibiotic therapy. …”
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Exploring LLMs Applications in Law: A Literature Review on Current Legal NLP Approaches by Marco Siino, Mariana Falco, Daniele Croce, Paolo Rosso

“…To identify the current state of the applications of Transformers (also known as Large Language Models or LLMs) in the legal domain, we analysed the existing literature from 2017 to 2023 through a database search and snowballing method. …”
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ChatGPT in healthcare education: a double-edged sword of trends, challenges, and opportunities by Michael Agyemang Adarkwah, Samuel Anokye Badu, Evans Appiah Osei, Enoch Adu-Gyamfi, Jonathan Odame, Käthe Schneider

“…The scoping review, conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, utilized search terms such as “ChatGPT,” “GPT,” “natural language processing,” “large language models,” and “health education”. The review followed the five-stage framework outlined for organization and analysis. …”
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TepiSense: A Social Computing-Based Real-Time Epidemic Surveillance System Using Artificial Intelligence by Bilal Tahir, Muhammad Amir Mehmood

“…TepiSense compares the performance of 3 feature extraction techniques, 9 machine/deep learning models, and 3 Large Language Models (LLMs). To test the performance of our system, we build a dataset of Twitter Epidemic Surveillance Corpus (TESC) containing 23.9K English and 13K labelled Urdu tweets related to six diseases: COVID19, hepatitis, malaria, flu, dengue, and HIV/AIDS. …”
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Evolution of artificial intelligence in healthcare: a 30-year bibliometric study by Yaojue Xie, Yuansheng Zhai, Yuansheng Zhai, Guihua Lu, Guihua Lu

“…IntroductionIn recent years, the development of artificial intelligence (AI) technologies, including machine learning, deep learning, and large language models, has significantly supported clinical work. …”
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Comparing the performance of ChatGPT and ERNIE Bot in answering questions regarding liver cancer interventional radiology in Chinese and English contexts: A comparative study by Xue-ting Yuan, Chen-ye Shao, Zhen-zhen Zhang, Duo Qian

“…Introduction This study aims to critically assess the appropriateness and limitations of two prominent large language models (LLMs), enhanced representation through knowledge integration (ERNIE Bot) and chat generative pre-trained transformer (ChatGPT), in answering questions about liver cancer interventional radiology. …”
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