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1.
Diabetes Metab Syndr ; 18(2): 102946, 2024 Feb.
Article in English | MEDLINE | ID: mdl-38330745

ABSTRACT

BACKGROUND: Peer review is the established method for evaluating the quality and validity of research manuscripts in scholarly publishing. However, scientific peer review faces challenges as the volume of submitted research has steadily increased in recent years. Time constraints and peer review quality assurance can place burdens on reviewers, potentially discouraging their participation. Some artificial intelligence (AI) tools might assist in relieving these pressures. This study explores the efficiency and effectiveness of one of the artificial intelligence (AI) chatbots, ChatGPT (Generative Pre-trained Transformer), in the peer review process. METHODS: Twenty-one peer-reviewed research articles were anonymised to ensure unbiased evaluation. Each article was reviewed by two humans and by versions 3.5 and 4.0 of ChatGPT. The AI was instructed to provide three positive and three negative comments on the articles and recommend whether they should be accepted or rejected. The human and AI results were compared using a 5-point Likert scale to determine the level of agreement. The correlation between ChatGPT responses and the acceptance or rejection of the papers was also examined. RESULTS: Subjective review similarity between human reviewers and ChatGPT showed a mean score of 3.6/5 for ChatGPT 3.5 and 3.76/5 for ChatGPT 4.0. The correlation between human and AI review scores was statistically significant for ChatGPT 3.5, but not for ChatGPT 4.0. CONCLUSION: ChatGPT can complement human scientific peer review, enhancing efficiency and promptness in the editorial process. However, a fully automated AI review process is currently not advisable, and ChatGPT's role should be regarded as highly constrained for the present and near future.


Subject(s)
Artificial Intelligence , Time Pressure , Humans , Pressure
2.
Br J Radiol ; 97(1156): 747-756, 2024 Mar 28.
Article in English | MEDLINE | ID: mdl-38346703

ABSTRACT

OBJECTIVE: To report the incidence of indeterminate pulmonary nodules (IPN) and the rate of progression of IPNs to metastasis in patients with primary bone cancers. We also aimed to evaluate clinical or radiological parameters that may identify IPNs more likely to progress to metastatic disease and their effect on overall or event-free survival in patients with primary bone sarcoma. METHODS: A systematic search of the electronic databases Medline, Embase, and Cochrane Library was undertaken for eligible articles on IPNs in patients with primary bone sarcomas, published in the English language from inception of the databases to 2023. The Newcastle-Ottawa Quality Assessment Form for Cohort Studies was utilized to evaluate risk of bias in included studies. RESULTS: Six studies, involving 1667 patients, were included in this systematic review. Pooled quantitative analysis found the rate of incidence of IPN to be 18.1% (302 out of 1667) and the rate of progression to metastasis to be 45.0% (136 out of 302). Nodule size (more than 5 mm diameter), number (more than or equal to 4), distribution (bilaterally distributed), incomplete calcification, and lobulated margins were associated with an increased likelihood of IPNs progressing to metastasis, however, their impact on overall or event-free survival remains unclear. CONCLUSION: The risk of IPNs progressing to metastasis in patients with primary bone sarcoma is non-negligible. Large IPNs have a high risk to be an actual metastasis. We suggest that IPNs in these patients be followed up for a minimum of 2 years with CT imaging at 3, 6, and 12 month intervals, particularly for nodules measuring >5 mm in average diameter. ADVANCES IN KNOWLEDGE: This is the first systematic review on IPNs in patients with primary bone sarcomas only and proposes viable management strategies for such patients.


Subject(s)
Bone Neoplasms , Lung Neoplasms , Multiple Pulmonary Nodules , Osteosarcoma , Sarcoma , Humans , Lung Neoplasms/pathology , Clinical Relevance , Multiple Pulmonary Nodules/pathology , Bone Neoplasms/diagnostic imaging , Sarcoma/diagnostic imaging , Osteosarcoma/diagnostic imaging
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