World Journal of Urology, Год журнала: 2023, Номер 41(9), С. 2573 - 2574
Опубликована: Авг. 10, 2023
Язык: Английский
World Journal of Urology, Год журнала: 2023, Номер 41(9), С. 2573 - 2574
Опубликована: Авг. 10, 2023
Язык: Английский
Korean Journal of Radiology, Год журнала: 2023, Номер 24(10), С. 952 - 952
Опубликована: Янв. 1, 2023
Large language models (LLMs) such as ChatGPT have garnered considerable interest for their potential to aid non-native English-speaking researchers. These can function personal, round-the-clock English tutors, akin how Prometheus in Greek mythology bestowed fire upon humans advancement. LLMs be particularly helpful researchers writing the Introduction and Discussion sections of manuscripts, where they often encounter challenges. However, using generate text research manuscripts entails concerns hallucination, plagiarism, privacy issues; mitigate these risks, authors should verify accuracy generated content, employ similarity detectors, avoid inputting sensitive information into prompts. Consequently, it may more prudent utilize editing refining rather than generating large portions text. Journal policies concerning use vary, but transparency disclosing artificial intelligence tool usage is emphasized. This paper aims summarize lower barrier academic English, enabling concentrate on domain-specific research, provided are used responsibly cautiously.
Язык: Английский
Процитировано
47Journal of Korean Medical Science, Год журнала: 2023, Номер 38(38)
Опубликована: Янв. 1, 2023
With emergence of chatbots to help authors with scientific writings, editors should have tools identify artificial intelligence-generated texts. GPTZero is among the first websites that has sought media attention claiming differentiate machine-generated from human-written
Язык: Английский
Процитировано
23Journal of Korean Medical Science, Год журнала: 2024, Номер 39(33)
Опубликована: Янв. 1, 2024
The application of new technologies, such as artificial intelligence (AI), to science affects the way and methodology in which research is conducted. While responsible use AI brings many innovations benefits humanity, its unethical poses a serious threat scientific integrity literature. Even absence malicious use, Chatbot output itself, software based on AI, carries risk containing biases, distortions, irrelevancies, misrepresentations plagiarism. Therefore, complex algorithms raises concerns about bias, transparency accountability, requiring development ethical rules protect integrity. Unfortunately, writing codes cannot keep up with pace implementation technology. main purpose this narrative review inform readers, authors, reviewers editors approaches publication ethics era AI. It specifically focuses tips how disclose your manuscript, avoid publishing entirely AI-generated text, current standards for retraction.
Язык: Английский
Процитировано
9Journal of Korean Medical Science, Год журнала: 2024, Номер 39(16)
Опубликована: Янв. 1, 2024
Although discharge summaries in patient-friendly language can enhance patient comprehension and satisfaction, they also increase medical staff workload. Using a large model, we developed validated software that generates summary.
Язык: Английский
Процитировано
4Journal of Korean Medical Science, Год журнала: 2025, Номер 40(7)
Опубликована: Янв. 1, 2025
The rapid advancement of artificial intelligence (AI) has transformed various aspects scientific research, including academic publishing and peer review. In recent years, AI tools such as large language models have demonstrated their capability to streamline numerous tasks traditionally handled by human editors reviewers. These applications range from automated grammar checks plagiarism detection, format compliance, even preliminary assessment research significance. While substantially benefits the efficiency accuracy processes, its integration raises critical ethical methodological questions, particularly in lacks subtle understanding complex content that expertise provides, posing challenges evaluating novelty Additionally, there are risks associated with over-reliance on AI, potential biases algorithms, concerns related transparency, accountability, data privacy. This review evaluates perspectives within community integrating publishing. By exploring both AI's limitations, we aim offer practical recommendations ensure is used a supportive tool, supporting but not replacing expertise. Such guidelines essential for preserving integrity quality work while benefiting efficiencies editorial processes.
Язык: Английский
Процитировано
0Medicine, Год журнала: 2025, Номер 104(8), С. e41594 - e41594
Опубликована: Фев. 21, 2025
The emergence of artificial intelligence (AI)-based linguistic models has revolutionized academic writing, prompting concerns about integrity. In response, AI-powered text authenticity detectors have been developed. This study examines AI tool usage in anesthesiology and intensive care journals. 1268 articles from 86 journals “Anesthesiology” “Anesthesiology Intensive Care” were analyzed using Copyleaks ZeroGPT. English abstracts published between April 18 May 18, 2023, scrutinized. ZeroGPT found average at 25.1% ± 27.5 10.5% 15.9, respectively. 16.8% “human-written,” while 83.2% “AI-assisted”. assistance correlated positively with abstract length was more common among nonnative speakers ( P < .001). It also prevalent high-impact science citation index-indexed .01; underscores the widespread adoption tools particularly authors journals, emphasizing need for improved detection mechanisms regulatory guidelines.
Язык: Английский
Процитировано
0Journal of Korean Medical Science, Год журнала: 2024, Номер 39(32)
Опубликована: Янв. 1, 2024
Reporting standards are essential to health research as they improve accuracy and transparency. Over time, significant changes have occurred the requirements for reporting ensure comprehensive transparent across a range of study domains foster methodological rigor. The establishment Declaration Helsinki, Consolidated Standards Trials (CONSORT), Strengthening Observational Studies in Epidemiology (STROBE), Preferred Items Systematic Reviews Meta-Analysis (PRISMA) just few historic initiatives that increased Through enhanced discoverability, statistical analysis facilitation, article quality enhancement, language barrier reduction, artificial intelligence (AI)-in particular, large models like ChatGPT-has transformed academic writing. However, problems with errors could occur need transparency while utilizing AI tools still exist. Modifying rules include AI-driven writing such ChatGPT is ethically practically challenging. In writing, precautions truth, privacy, responsibility necessary due concerns about biases, openness, data limits, potential legal ramifications. CONSORT-AI Standard Protocol Items: Recommendations Interventional (SPIRIT)-AI Steering Group expands CONSORT guidelines clinical trials-new checklists METRICS CLEAR help promote studies. Responsible usage technology software adoption requires interdisciplinary collaboration ethical assessment. This explores impact technologies, specifically ChatGPT, on past revised open, reproducible, robust scientific publications.
Язык: Английский
Процитировано
2Journal of Korean Medical Science, Год журнала: 2023, Номер 38(31)
Опубликована: Янв. 1, 2023
Plagiarism is among commonly identified scientific misconducts in submitted manuscripts. Some journals routinely check the level of text similarity manuscripts at time submission and reject on fly if score exceeds a set cut-off value (
Язык: Английский
Процитировано
5Journal of Korean Medical Science, Год журнала: 2023, Номер 38(27)
Опубликована: Янв. 1, 2023
Язык: Английский
Процитировано
4Rheumatology International, Год журнала: 2024, Номер 44(11), С. 2315 - 2325
Опубликована: Июль 16, 2024
Artificial intelligence algorithms, with roots extending into the past but experiencing a resurgence and evolution in recent years due to their superiority over traditional methods contributions human capabilities, have begun make presence felt field of pediatric rheumatology. In ever-evolving realm rheumatology, there been incremental advancements supported by artificial understanding stratifying diseases, developing biomarkers, refining visual analyses, facilitating individualized treatment approaches. However, like many other domains, these strides yet gain clinical applicability validation, ethical issues remain unresolved. Furthermore, mastering different novel terminologies appears challenging for clinicians. This review aims provide comprehensive overview current literature, categorizing algorithms applications, thus offering fresh perspective on nascent relationship between rheumatology intelligence, highlighting both its constraints.
Язык: Английский
Процитировано
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