Results 1 to 10 of about 10,528 (144)

Assessing the reliability and relevance of DeepSeek in EFL writing evaluation: a generalizability theory approach

Language Testing in Asia
This study explored the potential of DeepSeek to contribute to English writing assessment via generalizability (G-) theory and qualitative feedback analysis.
Melor Md Yunus, Harwati Hashim
exaly   +2 more sources

DeepSeek-R1 for automated scoring in radiology residency examinations: an agreement and test–retest reliability study

BMC Medical Education
Objective This study evaluates the feasibility of employing DeepSeek-R1 for automated scoring in examinations for radiology residents, comparing its performance with that of radiologists.
Guojie Wang, Yingqin Li
exaly   +2 more sources

Efectividad de DeepSeek V3 para la extracción terminológica y la traducción automática de Komposita alemanes sobre cardiología y su aplicación para la alfabetización en salud

Estudios de Lingüística
Este trabajo tiene como objetivo fundamental comprobar la efectividad de un modelo lingüístico de gran capacidad, de inteligencia artificial generativa, como DeepSeek-V3, que es similar a los ya conocidos ChatGPT, Copilot o Gemini, y que, al igual que ...
María del Carmen Balbuena Torezano
doaj   +1 more source

Evaluating AI Text Detection Tools for Distinguishing Human-Written from AI-Generated Abstracts in Persian-Language Journals of Library and Information Science

Acta Informatica Pragensia
Background: Researchers are using artificial intelligence (AI) tools in academic writing. However, their use may compromise the integrity and originality of the work. Hence, AI text detection tools have come to increase transparency.
Amrollah Shamsi, Ting Wang, Maryam Amraei, Narayanaswamy Vasantha Raju   +3 more
doaj   +1 more source

Comparing closed and open large language models on pediatric cardiology board exam performance

Annals of Pediatric Cardiology
Large language models (LLMs) have gained traction in medicine, but there is limited research comparing closed- and open-source models in subspecialty contexts.
Nino Nikolovski, Conall T. Morgan, Michael N. Gritti   +2 more
doaj   +1 more source

When Large Language Models (LLMs) walk into a Bachelor’s in optometry examination: Comparing the performances of LLMs and bachelor of optometry students

Indian Journal of Ophthalmology
Purpose: To evaluate the performance of Large Language Models (LLMs) on optometry examination questions and compare their accuracy and readability with Bachelor of Optometry students.
Atul Arora, Uday Pratap Singh Parmar, Anjali, Pragati Mathur, Kamal Kishore, Usha Singh, Surinder Singh Pandav, Vishali Gupta   +7 more
doaj   +1 more source

The role of artificial intelligence in academic citation: A study on lens, cataract, and anterior segment research

Indian Journal of Ophthalmology
Purpose: To evaluate the accuracy and reliability of four artificial intelligence (AI) models—ChatGPT, Copilot, DeepSeek, and Gemini—in generating PubMed citations for literature related to lens disease, cataracts, iris disorders, and anterior chamber ...
Mustafa Civelekler, Mehmet Çıtırık
doaj   +1 more source

Teaching agricultural university students writing professional essays based on practice using generative artificial intelligence

Вестник Тамбовского университета. Серия: Гуманитарные науки
Importance. Generative artificial intelligence tools are actively replacing tools that we have been accustomed to using for decades in all areas of life.
K. V. Kapranchikova, E. L. Zavgorodnyaya
doaj   +1 more source

AI-Powered Idiom Translation Between English and Arabic: A Comparative Study of ChatGPT, DeepSeek, and Gemini

Dialogica
This study investigates the performance of three AI-powered translation tools – ChatGPT, DeepSeek, and Gemini – in translating idiomatic expressions between English and Arabic.
Hamza Belfassi, Yassine Elfaizi, Zahra El Aouri   +2 more
doaj   +1 more source

Hyperparameter Optimization of IndoBERT for DeepSeek User Sentiment Analysis

Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
This study aims to evaluate the performance of the IndoBERT model in sentiment classification of user reviews for the DeepSeek application on the Google Play Store.
Andro Nicus Saragih, Lisnawita*
doaj   +1 more source