The Applications of Large Language Models in Mental Health: Scoping Review by Yu Jin, Jiayi Liu, Pan Li, Baosen Wang, Yangxinyu Yan, Huilin Zhang, Chenhao Ni, Jing Wang, Yi Li, Yajun Bu, Yuanyuan Wang

“…Studies were excluded if they (1) were not peer-reviewed or did not focus on mental health or mental disorders or (2) did not use LLMs; studies that used only natural language processing or long short-term memory models were also excluded. …”
Get full text

Patient Voices in Dialysis Care: Sentiment Analysis and Topic Modeling Study of Social Media Discourse by Ravi Shankar, Qian Xu, Anjali Bundele

“…ObjectiveThis study aimed to uncover key themes, emotions, and challenges expressed by the dialysis community on X from April 2006 to August 2024 by leveraging natural language processing techniques, specifically sentiment analysis and topic modeling. …”
Get full text

Exploring Psychosocial Burdens of Diabetes in Pregnancy and the Feasibility of Technology-Based Support: Qualitative Study by Maya V Roytman, Layna Lu, Elizabeth Soyemi, Karolina Leziak, Charlotte M Niznik, Lynn M Yee

“…Future incorporation of machine learning and language processing models in the app may provide further personalization of recommendations and education for individuals with DM during pregnancy. …”
Get full text

Optimizing translation for low-resource languages: Efficient fine-tuning with custom prompt engineering in large language models by Pitso Walter Khoboko, Vukosi Marivate, Joseph Sefara

“…However, the emergence of new Parameter-Efficient Fine-Tuning (PEFT) strategies provides a cost-effective approach to unlocking the potential of LLMs across a variety of natural language processing (NLP) tasks. In this study, we selected the Mistral 7B language model as our primary LLM due to its superior performance, which surpasses that of LLAMA 2 13B across multiple benchmarks. …”
Get full text

AI-generated draft replies to patient messages: exploring effects of implementation by Charlotte M. H. H. T. Bootsma-Robroeks, Charlotte M. H. H. T. Bootsma-Robroeks, Jessica D. Workum, Jessica D. Workum, Stephanie C. E. Schuit, Anne Hoekman, Tarannom Mehri, Job N. Doornberg, Job N. Doornberg, Tom P. van der Laan, Tom P. van der Laan, Rosanne C. Schoonbeek, Rosanne C. Schoonbeek

“…The adoption rate, the level of adjustments to the initial drafted responses compared to the final sent messages (using ROUGE-1 and BLEU-1 natural language processing scores), and the time spent on these adjustments were analyzed.ResultsA total of 919 messages by 100 physicians were evaluated. …”
Get full text

Impact of Medical Conditions and Area Deprivation on Fundraising Success in Online Crowdfunding: Cross-Sectional Study by Steven S Doerstling, Matthew M Engelhard, Dennis Akrobetu, Caroline E Sloan, Ada Campagna, Thuy-Vi Nguyen, Farrah Madanay, Felicia Chen, Peter A Ubel

“…Using a previously validated disease identification algorithm based on natural language processing, we identified the presence or absence of 11 broad disease categories in each campaign description. …”
Get full text

Real-Time, Risk-Based Clinical Trial Quality Management in China: Development of a Digital Monitoring Platform by Min Jiang, Shuhua Zhao, Yun Mei, Zhiying Fu, Yannan Yuan, Jie Ai, Yuan Sheng, Ying Gong, Jingjing Chen

“…QC report text was processed by using an automated natural language processing tool. All QC reports were grouped into 2 clusters via hierarchical clustering analysis. …”
Get full text

Observational study of sudden cardiac arrest risk (OSCAR): Rationale and design of an electronic health records cohort by Kyndaron Reinier, Harpriya S. Chugh, Audrey Uy-Evanado, Elizabeth Heckard, Marco Mathias, Nichole Bosson, Vinicius F. Calsavara, Piotr J. Slomka, David A. Elashoff, Alex A.T. Bui, Sumeet S Chugh

“…We will use conventional approaches (diagnosis code algorithms) and artificial intelligence (natural language processing, deep learning) to define patient phenotypes and biostatistical and machine learning approaches for analysis. …”
Get full text

Entity-level cross-modal fusion for multimodal chinese agricultural diseases and pests named entity recognition by Jingzhong Huang, Xia Hao, Yu Wang, Ruizhi Song, Zenan Mu, Wen Chu, Georgios Papadakis, Sijie Niu, Xuchao Guo

“…(NER), as one of the popular directions in natural language processing, plays a critical role in fields such as information extraction and agricultural knowledge graph construction. …”
Get full text

AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women by Li Ma, Li Ma, Ru Chen, Weigong Ge, Paul Rogers, Beverly Lyn-Cook, Huixiao Hong, Weida Tong, Ningning Wu, Wen Zou

“…Topic modeling is a crucial technique in natural language processing (NLP), enabling the extraction of latent themes from large text corpora. …”
Get full text

Detecting schizophrenia, bipolar disorder, psychosis vulnerability and major depressive disorder from 5 minutes of online-collected speech by Julianna Olah, Win Lee Edwin Wong, Atta-ul Raheem Rana Chaudhry, Omar Mena, Sunny X. Tang

“…Recent advancements in Natural Language Processing (NLP) methodologies enable the automated extraction of informative speech features, which has been leveraged for early psychosis detection and assessment of symptomology. …”
Get full text

Bias Mitigation in Primary Health Care Artificial Intelligence Models: Scoping Review by Maxime Sasseville, Steven Ouellet, Caroline Rhéaume, Malek Sahlia, Vincent Couture, Philippe Després, Jean-Sébastien Paquette, David Darmon, Frédéric Bergeron, Marie-Pierre Gagnon

“…Algorithmic preprocessing methods, such as relabeling and reweighing data, along with natural language processing techniques that extract data from unstructured notes, showed the greatest potential for bias mitigation. …”
Get full text

Cross-language orthographic neighborhood density effects in Dutch–English and Spanish–English bilinguals by Britta Biedermann, Britta Biedermann, Elisabeth Beyersmann, Mara Blosfelds, Christella Macapagal, Ashleigh Rosevear, Welber Marinovic

“…Precise mechanisms for influencing variables within L2 and cross-language processing are still little understood. The current visual word recognition study explored orthographic neighborhood density (ND) effects in L2 English, replicating the effects for Dutch–English while expanding the exploration to a new language combination, Spanish–English. …”
Get full text

A Multi-Head Attention-Based Transformer Model for Predicting Causes in Aviation Incidents by Aziida Nanyonga, Hassan Wasswa, Keith Joiner, Ugur Turhan, Graham Wild

“…To streamline investigations, scholars advocate for natural language processing (NLP) and topic modelling methodologies, which organize pertinent aviation terms for rapid analysis. …”
Get full text

The linguocultural concept of 疫/pandemic/пaндeмия in Chinese, English, and Russian linguistic consciousness by Yanlei Ge

“…Based on the theory of linguocultural concepts, the study employed natural language processing methods such as the analysis of word frequency and collocation co-occurrence to conduct an in-depth empirical study of 疫/pandemic/пaндeмия as a linguocultural concept in Chinese, English, and Russian linguistic consciousness from diachronic and synchronic perspectives. …”
Get full text

Application of artificial intelligence in palliative care: a bibliometric analysis of research hotspots and trends by Mingxia Pan, Mingxia Pan, Renling Huang, Chenxi Liu, Yuanfang Xiong, Na Li, Huan Peng, Yongqi Liang, Weisheng Gu, Hanjiao Liu, Hanjiao Liu

“…Technological analyses reveal that machine learning, deep learning, and natural language processing are becoming increasingly significant in palliative care. …”
Get full text

Artificial Intelligence-Assisted Clinical Decision-Making: A Perspective on Advancing Personalized Precision Medicine for Elderly Diabetes Patients by Hu J, Ren L, Wang T, Yao P

“…Through systematic analysis of current healthcare practices and emerging AI technologies, we examined the integration of machine learning algorithms, natural language processing, and intelligent monitoring systems into diabetes care for elderly populations. …”
Get full text

Automated Pathologic TN Classification Prediction and Rationale Generation From Lung Cancer Surgical Pathology Reports Using a Large Language Model Fine-Tuned With Chain-of-Thought... by Sanghwan Kim, Sowon Jang, Borham Kim, Leonard Sunwoo, Seok Kim, Jin-Haeng Chung, Sejin Nam, Hyeongmin Cho, Donghyoung Lee, Keehyuck Lee, Sooyoung Yoo

“… BackgroundTraditional rule-based natural language processing approaches in electronic health record systems are effective but are often time-consuming and prone to errors when handling unstructured data. …”
Get full text

Patient-Reported Symptoms Compared With Nephrologist Documentation During Outpatient Visits: A Retrospective Patient-Reported Outcome Measures Study by Kendra E. Wulczyn, Annie Liu, James P. Lash, Mallika L. Mendu, Sahir Kalim

“…Symptoms were identified in the EHR-based note by natural language processing with subsequent manual identification of the context. …”
Get full text

Comparison of medical history documentation efficiency and quality based on GPT-4o: a study on the comparison between residents and artificial intelligence by Xiaojing Lu, Xinqi Gao, Xinyi Wang, Zhenye Gong, Jie Cheng, Weiguo Hu, Shaun Wu, Rong Wang, Xiaoyang Li

“…Artificial Intelligence (AI) technologies, particularly advances in Natural Language Processing (NLP), have introduced new possibilities for medical documentation. …”
Get full text