From Web to RheumaLpack: Creating a Linguistic Corpus for Exploitation and Knowledge Discovery in Rheumatology DOI Creative Commons
Alfredo Madrid-García, Beatriz Merino‐Barbancho, D. Freites

et al.

Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 179, P. 108920 - 108920

Published: July 23, 2024

This study introduces RheumaLinguisticpack (RheumaLpack), the first specialised linguistic web corpus designed for field of musculoskeletal disorders. By combining mining (i.e., scraping) and natural language processing (NLP) techniques, as well clinical expertise, RheumaLpack systematically captures curates structured unstructured data across a spectrum sources including trials registers ClinicalTrials.gov), bibliographic databases PubMed), medical agencies (i.e. European Medicines Agency), social media Reddit), accredited health websites MedlinePlus, Harvard Health Publishing, Cleveland Clinic). Given complexity rheumatic diseases (RMDs) their significant impact on quality life, this resource can be proposed useful tool to train algorithms that could mitigate diseases' effects. Therefore, aims improve training artificial intelligence (AI) facilitate knowledge discovery in RMDs. The development involved systematic six-step methodology covering identification, characterisation, selection, collection, processing, description. result is non-annotated, monolingual, dynamic corpus, featuring almost 3 million records spanning from 2000 2023. represents pioneering contribution rheumatology research, providing advanced AI NLP applications. highlights value address challenges posed by diseases, illustrating corpus's potential research treatment paradigms rheumatology. Finally, shown replicated obtain other specialities. code details how build are also provided dissemination such resource.

Language: Английский

Generative artificial intelligence in healthcare: A scoping review on benefits, challenges and applications DOI
Khadijeh Moulaei,

Atiye Yadegari,

Mahdi Baharestani

et al.

International Journal of Medical Informatics, Journal Year: 2024, Volume and Issue: 188, P. 105474 - 105474

Published: May 8, 2024

Language: Английский

Citations

44
Comparative accuracy of ChatGPT-4, Microsoft Copilot and Google Gemini in the Italian entrance test for healthcare sciences degrees: a cross-sectional study DOI Creative Commons
Giacomo Rossettini,

Lia Rodeghiero,

Federica Corradi

et al.

BMC Medical Education, Journal Year: 2024, Volume and Issue: 24(1)

Published: June 26, 2024

Abstract Background Artificial intelligence (AI) chatbots are emerging educational tools for students in healthcare science. However, assessing their accuracy is essential prior to adoption settings. This study aimed assess the of predicting correct answers from three AI (ChatGPT-4, Microsoft Copilot and Google Gemini) Italian entrance standardized examination test science degrees (CINECA test). Secondarily, we assessed narrative coherence chatbots’ responses (i.e., text output) based on qualitative metrics: logical rationale behind chosen answer, presence information internal question, external question. Methods An observational cross-sectional design was performed September 2023. Accuracy evaluated CINECA test, where questions were formatted using a multiple-choice structure with single best answer. The outcome binary (correct or incorrect). Chi-squared post hoc analysis Bonferroni correction differences among performance accuracy. A p -value < 0.05 considered statistically significant. sensitivity performed, excluding that not applicable (e.g., images). Narrative analyzed by absolute relative frequencies errors. Results Overall, 820 inputted into all chatbots, 20 imported ChatGPT-4 ( n = 808) Gemini due technical limitations. We found significant vs comparisons 0.001). revealed “Logical reasoning” as prevalent answer 622, 81.5%) error” incorrect 40, 88.9%). Conclusions Our main findings reveal that: (A) well; (B) better than Gemini; (C) primarily logical. Although showed promising university encourage candidates cautiously incorporate this new technology supplement learning rather primary resource. Trial registration Not required.

Language: Английский

Citations

22
A framework for human evaluation of large language models in healthcare derived from literature review DOI Creative Commons

Thomas Yu Chow Tam,

Sonish Sivarajkumar,

Sumit Kapoor

et al.

npj Digital Medicine, Journal Year: 2024, Volume and Issue: 7(1)

Published: Sept. 28, 2024

Abstract With generative artificial intelligence (GenAI), particularly large language models (LLMs), continuing to make inroads in healthcare, assessing LLMs with human evaluations is essential assuring safety and effectiveness. This study reviews existing literature on evaluation methodologies for healthcare across various medical specialties addresses factors such as dimensions, sample types sizes, selection, recruitment of evaluators, frameworks metrics, process, statistical analysis type. Our review 142 studies shows gaps reliability, generalizability, applicability current practices. To overcome significant obstacles LLM developments deployments, we propose QUEST, a comprehensive practical framework covering three phases workflow: Planning, Implementation Adjudication, Scoring Review. QUEST designed five proposed principles: Quality Information, Understanding Reasoning, Expression Style Persona, Safety Harm, Trust Confidence.

Language: Английский

Citations

17
AI-driven translations for kidney transplant equity in Hispanic populations DOI Creative Commons
Oscar A. Garcia Valencia, Charat Thongprayoon, Caroline C. Jadlowiec

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: April 12, 2024

Abstract Health equity and accessing Spanish kidney transplant information continues being a substantial challenge facing the Hispanic community. This study evaluated ChatGPT’s capabilities in translating 54 English frequently asked questions (FAQs) into using two versions of AI model, GPT-3.5 GPT-4.0. The FAQs included 19 from Organ Procurement Transplantation Network (OPTN), 15 National Service (NHS), 20 Kidney Foundation (NKF). Two native Spanish-speaking nephrologists, both whom are Mexican heritage, scored translations for linguistic accuracy cultural sensitivity tailored to Hispanics 1–5 rubric. inter-rater reliability evaluators, measured by Cohen’s Kappa, was 0.85. Overall 4.89 ± 0.31 versus 4.94 0.23 GPT-4.0 (non-significant p = 0.23). Both 4.96 0.19 (p 1.00). By source, 4.84 0.37 4.93 0.26 4.90 4.95 0.22 For sensitivity, 5.00 0.00 (NKF), while These high scores demonstrate Chat GPT effectively translated across systems. findings suggest GPT’s potential promote health improving access essential information. Additional research should evaluate its medical translation diverse contexts/languages. English-to-Spanish may increase vital underserved patients.

Language: Английский

Citations

12
A comparative study of English and Japanese ChatGPT responses to anaesthesia-related medical questions DOI Creative Commons
Kazuo Ando,

Sato Masaki,

Shin Wakatsuki

et al.

BJA Open, Journal Year: 2024, Volume and Issue: 10, P. 100296 - 100296

Published: June 1, 2024

Language: Английский

Citations

8
Artificial intelligence in rheumatology research: what is it good for? DOI Creative Commons
José Miguel Sequí-Sabater, Diego Benavent

RMD Open, Journal Year: 2025, Volume and Issue: 11(1), P. e004309 - e004309

Published: Jan. 1, 2025

Artificial intelligence (AI) is transforming rheumatology research, with a myriad of studies aiming to improve diagnosis, prognosis and treatment prediction, while also showing potential capability optimise the research workflow, drug discovery clinical trials. Machine learning, key element discriminative AI, has demonstrated ability accurately classifying rheumatic diseases predicting therapeutic outcomes by using diverse data types, including structured databases, imaging text. In parallel, generative driven large language models, becoming powerful tool for optimising workflow supporting content generation, literature review automation decision support. This explores current applications future both AI in rheumatology. It highlights challenges posed these technologies, such as ethical concerns need rigorous validation regulatory oversight. The integration promises substantial advancements but requires balanced approach benefits minimise possible downsides.

Language: Английский

Citations

1
Evaluating AI performance in nephrology triage and subspecialty referrals DOI Creative Commons

Priscilla Koirala,

Charat Thongprayoon,

Jing Miao

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 27, 2025

Language: Английский

Citations

1
Multimodal Generative Artificial Intelligence Tackles Visual Problems in Chemistry DOI

Eman A. Alasadi,

Carlos R. Baiz

Journal of Chemical Education, Journal Year: 2024, Volume and Issue: 101(7), P. 2716 - 2729

Published: June 26, 2024

The introduction of multimodal capabilities in large language models (LLMs) marks a significant advancement the field artificial intelligence (AI). In particular, ability to process and interpret visual data, including complex graphs plots frequently encountered chemistry, expands potential these models. This integration text image processing allows AI tackle broader range problems, especially areas where information is central understanding solving problems. study provides an examination GPT-4's input capabilities, specifically targeting its efficacy interpreting chemistry problems that require graphical information. evaluates feature, focusing on accuracy chemical diagrams, structures, tabular utility as interactive, conversational tutor education. research assesses consistency AI's responses data varying quality parse handwritten answers. Further, examines capacity for molecular structure analysis spectral interpretation, vital advanced problem-solving chemistry. Through analysis, we demonstrate how GPT-4 could be leveraged pedagogical purposes, particularly undergraduate courses. addition, provide advice prompt development improve response quality.

Language: Английский

Citations

6
Ethical Considerations and Fundamental Principles of Large Language Models in Medical Education: Viewpoint DOI Creative Commons
Li Zhui, Fenghe Li,

Xuehu Wang

et al.

Journal of Medical Internet Research, Journal Year: 2024, Volume and Issue: 26, P. e60083 - e60083

Published: July 7, 2024

This viewpoint article first explores the ethical challenges associated with future application of large language models (LLMs) in context medical education. These include not only concerns related to development LLMs, such as artificial intelligence (AI) hallucinations, information bias, privacy and data risks, deficiencies terms transparency interpretability but also issues concerning including emotional intelligence, educational inequities, problems academic integrity, questions responsibility copyright ownership. paper then analyzes existing AI-related legal frameworks highlights their limitations regard LLMs To ensure that are integrated a responsible safe manner, authors recommend unified framework is specifically tailored for this field. should be based on 8 fundamental principles: quality control supervision mechanisms; protection; interpretability; fairness equal treatment; integrity moral norms; accountability traceability; protection respect intellectual property; promotion research innovation. The further discuss specific measures can taken implement these principles, thereby laying solid foundation comprehensive actionable framework. Such principles provide clear guidance support approach help establish balance between technological advancement safeguards, ensuring education progress without compromising fairness, justice, or patient safety establishing more equitable, safer, efficient environment

Language: Английский

Citations

6
Performance of ChatGPT-3.5 and ChatGPT-4 on the European Board of Urology (EBU) exams: a comparative analysis DOI

Justine Schoch,

H. U. Schmelz,

Angelina Strauch

et al.

World Journal of Urology, Journal Year: 2024, Volume and Issue: 42(1)

Published: July 26, 2024

Language: Английский

Citations

6