{"title":"人工智能在期刊投稿内部道德检查中的应用前景。","authors":"Fatima Alnaimat, Abdel Rahman Feras AlSamhori, Omar Hamdan, Birzhan Seiil, Ainur B Qumar","doi":"10.3346/jkms.2025.40.e170","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence (AI) has shown its ability to transform academic writing and publishing. It offers significant benefits, including enhancing efficiency, consistency, and integrity, However, these advancements are accompanied by ethical concerns (particularly around authorship, originality, and transparency) and the need for human oversight in peer review and editorial processes. In this study we explore AI for ethics checks in journal submissions. Specific AI platforms-such as YesChat for bias detection, Turnitin's iThenticate for plagiarism, Proofig for image integrity, and GPTZero for AI-generated content-can identify ethical breaches through tailored prompts and queries. Additionally, AI is increasingly used to detect missing or vague ethics statements, conflicts of interest, and citation manipulation by analyzing structured text and databases. AI-enhanced tools like Elsevier's Editorial Manager and Enago Read assist in ensuring compliance with journal-specific ethical guidelines and streamline peer review. Moreover, emerging algorithms, such as CIDRE, have shown promise in identifying abnormal citation behaviors. As AI accuracy improves, these platforms are expected to be integrated directly into submission systems, enhancing research integrity, transparency, and accountability.</p>","PeriodicalId":16249,"journal":{"name":"Journal of Korean Medical Science","volume":"40 21","pages":"e170"},"PeriodicalIF":3.0000,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12133599/pdf/","citationCount":"0","resultStr":"{\"title\":\"Perspectives of Artificial Intelligence Use for In-House Ethics Checks of Journal Submissions.\",\"authors\":\"Fatima Alnaimat, Abdel Rahman Feras AlSamhori, Omar Hamdan, Birzhan Seiil, Ainur B Qumar\",\"doi\":\"10.3346/jkms.2025.40.e170\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Artificial intelligence (AI) has shown its ability to transform academic writing and publishing. It offers significant benefits, including enhancing efficiency, consistency, and integrity, However, these advancements are accompanied by ethical concerns (particularly around authorship, originality, and transparency) and the need for human oversight in peer review and editorial processes. In this study we explore AI for ethics checks in journal submissions. Specific AI platforms-such as YesChat for bias detection, Turnitin's iThenticate for plagiarism, Proofig for image integrity, and GPTZero for AI-generated content-can identify ethical breaches through tailored prompts and queries. Additionally, AI is increasingly used to detect missing or vague ethics statements, conflicts of interest, and citation manipulation by analyzing structured text and databases. AI-enhanced tools like Elsevier's Editorial Manager and Enago Read assist in ensuring compliance with journal-specific ethical guidelines and streamline peer review. Moreover, emerging algorithms, such as CIDRE, have shown promise in identifying abnormal citation behaviors. As AI accuracy improves, these platforms are expected to be integrated directly into submission systems, enhancing research integrity, transparency, and accountability.</p>\",\"PeriodicalId\":16249,\"journal\":{\"name\":\"Journal of Korean Medical Science\",\"volume\":\"40 21\",\"pages\":\"e170\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2025-06-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12133599/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Korean Medical Science\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3346/jkms.2025.40.e170\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Korean Medical Science","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3346/jkms.2025.40.e170","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Perspectives of Artificial Intelligence Use for In-House Ethics Checks of Journal Submissions.
Artificial intelligence (AI) has shown its ability to transform academic writing and publishing. It offers significant benefits, including enhancing efficiency, consistency, and integrity, However, these advancements are accompanied by ethical concerns (particularly around authorship, originality, and transparency) and the need for human oversight in peer review and editorial processes. In this study we explore AI for ethics checks in journal submissions. Specific AI platforms-such as YesChat for bias detection, Turnitin's iThenticate for plagiarism, Proofig for image integrity, and GPTZero for AI-generated content-can identify ethical breaches through tailored prompts and queries. Additionally, AI is increasingly used to detect missing or vague ethics statements, conflicts of interest, and citation manipulation by analyzing structured text and databases. AI-enhanced tools like Elsevier's Editorial Manager and Enago Read assist in ensuring compliance with journal-specific ethical guidelines and streamline peer review. Moreover, emerging algorithms, such as CIDRE, have shown promise in identifying abnormal citation behaviors. As AI accuracy improves, these platforms are expected to be integrated directly into submission systems, enhancing research integrity, transparency, and accountability.
期刊介绍:
The Journal of Korean Medical Science (JKMS) is an international, peer-reviewed Open Access journal of medicine published weekly in English. The Journal’s publisher is the Korean Academy of Medical Sciences (KAMS), Korean Medical Association (KMA). JKMS aims to publish evidence-based, scientific research articles from various disciplines of the medical sciences. The Journal welcomes articles of general interest to medical researchers especially when they contain original information. Articles on the clinical evaluation of drugs and other therapies, epidemiologic studies of the general population, studies on pathogenic organisms and toxic materials, and the toxicities and adverse effects of therapeutics are welcome.