Investigating the Prospects of ChatGPT in Training Medicinal Chemists and the Development of Novel Drugs by Michell O. Almeida, Artur C. G. Soares, Gustavo H. M. Sousa, Witor R. Ferraz, Gustavo Trossini

“…Alongside other large language models, this tool exhibits the potential to directly or indirectly assist in a range of scientific areas including Computer Science, Chemistry, Biology/Bioinformatics, and Medicine. …”
Get full text

AI for chemistry teaching: responsible AI and ethical considerations by Blonder Ron, Feldman-Maggor Yael

“…GenAI, driven by advanced AI models like Large Language Models, has shown substantial potential in generating educational content. …”
Get full text

Refining the prediction of user satisfaction on chat-based AI applications with unsupervised filtering of rating text inconsistencies by Hae Sun Jung, Jang Hyun Kim, Haein Lee

“…The swift development of artificial intelligence (AI) technology has triggered substantial changes, particularly evident in the emergence of chat-based services driven by large language models. With the increasing number of users utilizing these services, understanding and analysing user satisfaction becomes crucial for service improvement. …”
Get full text

LLM-based collaborative programming: impact on students’ computational thinking and self-efficacy by Yi-Miao Yan, Chuang-Qi Chen, Yang-Bang Hu, Xin-Dong Ye

“…To address these challenges, Large Language Models (LLMs) can be introduced as a supportive tool to enhance both the efficiency and outcomes of collaborative programming. …”
Get full text

ChatGPT and oral cancer: a study on informational reliability by Mesude Çi̇ti̇r

“…Abstract Background Artificial intelligence (AI) and large language models (LLMs) like ChatGPT have transformed information retrieval, including in healthcare. …”
Get full text

LLM-AIDSim: LLM-Enhanced Agent-Based Influence Diffusion Simulation in Social Networks by Lan Zhang, Yuxuan Hu, Weihua Li, Quan Bai, Parma Nand

“…This paper introduces an LLM-Enhanced Agent-Based Influence Diffusion Simulation (LLM-AIDSim) framework that integrates large language models (LLMs) into agent-based modelling to simulate influence diffusion in social networks. …”
Get full text

Source Code Error Understanding Using BERT for Multi-Label Classification by Md Faizul Ibne Amin, Yutaka Watanobe, Md Mostafizer Rahman, Atsushi Shirafuji

“…Additionally, we employed several combinations of large language models (CodeT5, CodeBERT) with machine learning classifiers (Decision Tree, Random Forest, Ensemble Learning, ML-KNN), demonstrating the superiority of our proposed approach. …”
Get full text

INTERPRETING METAPHORICAL LANGUAGE: A CHALLENGE TO ARTIFICIAL INTELLIGENCE by Inna V. Skrynnikova

“…Based on an overview of the existing studies findings in computational linguistics and related fields, the paper identifies a number of problems associated with the interpretation of non-literal expressions of language by large language models (LLM). It reveals that there is still no clear understanding of the methods for training language models to automatically recognize and interpret metaphors that would bring it closer to the level of human “interpretive competencies”. …”
Get full text

Artificial intelligence in CT diagnosis: Current status and future prospects for ear diseases by Ruowei Tang, Pengfei Zhao, Jia Li, Zhixiang Wang, Ning Xu, Zhenchang Wang

“…Furthermore, AI-driven natural language processing and large language models are revolutionizing the generation of radiology reports, providing accurate and standardized diagnostic information. …”
Get full text

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.…”
Get full text

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. …”
Get full text

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. …”
Get full text

Text mining of practical disaster reports: Case study on Cascadia earthquake preparedness. by Julia C Lensing, John Y Choe, Branden B Johnson, Jingwen Wang

“…Survey results highlight that while simple tools may yield insights that are primarily interpretable by experienced professionals, more advanced tools utilizing large language models, such as Generative Pre-trained Transformer (GPT), offer more accessible insights, albeit with known risk associated with current artificial intelligence technologies. …”
Get full text

Human-Centered AI for Migrant Integration Through LLM and RAG Optimization by Dagoberto Castellanos-Nieves, Luis García-Forte

“…Traditionally, the focus on algorithms alone has shifted toward a more comprehensive understanding of AI’s potential to shape technology in ways which better serve human needs, particularly for disadvantaged groups. Large language models (LLMs) and retrieval-augmented generation (RAG) offer significant potential to bridging gaps for vulnerable populations, including immigrants, refugees, and individuals with disabilities. …”
Get full text

Discriminative, generative artificial intelligence, and foundation models in retina imaging by Paisan Ruamviboonsuk, Niracha Arjkongharn, Nattaporn Vongsa, Pawin Pakaymaskul, Natsuda Kaothanthong

“…A foundation model, RETFound, which was self-supervised and found to discriminate many eye and systemic diseases better than supervised models. Large language models are foundation models that may be applied for text-related tasks, like reports of retinal angiography. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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.…”
Get full text

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. …”
Get full text

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. …”
Get full text