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Two researchers recommended this article for publication. I think this revised manuscript could be considered for publication in this journal, except that the following issues are addressed at the Proof stage:
In Table 2, [cindex] should be revised to [C-index], and [Overrall] should be revised to [Overall].
**PeerJ Staff Note:** Please ensure that all review, editorial, and staff comments are addressed in a response letter and any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate.
**PeerJ Staff Note:** Although the Academic Editor is happy to accept your article as being scientifically sound, a final check of the manuscript shows that it would benefit from further English editing. Therefore, please identify necessary edits and address these while in proof stage.
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Please respond and make appropriate revisions based on the Reviewers' suggestions and my comments (below). This will greatly improve the quality of this manuscript.
Here are my comments:
The main weakness of this article is that its Discussion section lacks some necessary explanations and natural transitions.
1. Line 231: [At the same time, machine learning has published many studies in the ICU population] should be revised to [machine learning has been applied to numerous studies in the ICU population].
2. The phrase "machine learning-based method for identifying AKI patients in the ICU has optimal application value" seems ambiguous. What is meant by "optimal application value"? This might need a clearer definition or explanation.
3. Discussion, paragraph 5: This paragraph suddenly introduces autoimmune diseases and their link to AKI. This seems a bit out of place and might need a smoother transition or introduction.
4. Discussion, paragraph 6: the statement "Secondly, the diversity of the included models has caused inevitable heterogeneity" could benefit from an explanation or elaboration about the implications of this heterogeneity on the results or interpretations.
5. Just as suggested by Reviewer 3, the authors need to clearly state in what aspects the advancement of this research fills the gaps of previous research
**PeerJ Staff Note:** Please ensure that all review and editorial comments are addressed in a response letter and any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate.
**Language Note:** The review process has identified that the English language must be improved. PeerJ can provide language editing services - please contact us at copyediting@peerj.com for pricing (be sure to provide your manuscript number and title). Alternatively, you should make your own arrangements to improve the language quality and provide details in your response letter. – PeerJ Staff
In the compelling manuscript entitled "Predictive value of machine learning for the risk of acute kidney injury (AKI) and inflammation in hospital ICU patients: a systematic review and meta-analysis," the authors have adroitly unearthed a machine learning-based methodology that exhibits remarkable efficacy in forecasting the risk of AKI among hospital ICU patients. This innovative approach not only boasts exceptional predictive accuracy but also holds the potential to serve as a strategic instrument for the prospective identification and preemptive management of inflammation. The manuscript, while poised for publication pending some revisions, stands as a significant contribution to the field.
In the methodological exposition, I recommend the inclusion of a statement elucidating the deliberate focus solely on English-language literature during the search process. This clarification will further refine the scope and parameters of the study, enhancing the precision of its findings.
Furthermore, I commend the authors for their insightful exploration; however, a comprehensive review of the manuscript's punctuation is warranted. Ensuring adherence to English punctuation conventions will not only bolster the readability of the document but also underscore its scholarly rigor.
To optimize the coherence of the manuscript's structure, I propose that the discussion section be initiated with a succinct presentation of the principal findings. This approach will provide readers with immediate access to the core results, enhancing their engagement and appreciation of the study's significance. Subsequently, within the discussion, a thorough assessment of the study's limitations and thoughtful suggestions for prospective research directions would enrich the manuscript's impact and scholarly value.
On a critical note, it is essential to acknowledge that the manuscript has been compromised by an array of typographical errors and grammatical inconsistencies, which collectively impede the clarity and professionalism of the presentation. Given these linguistic concerns, I strongly recommend that the manuscript undergo meticulous proofreading by a fluent English speaker, thereby rectifying these linguistic infelicities and fortifying the overall quality of the paper.
In conclusion, the authors' endeavors in deciphering the predictive potential of machine learning in the context of AKI risk assessment and inflammation prediction are undoubtedly commendable. The aforementioned refinements, once implemented, will elevate the manuscript to a level befitting its valuable insights and contributions, ultimately rendering it worthy of dissemination within the academic community.
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Engaging in a meticulous systematic review and comprehensive meta-analysis, the authors have effectively illuminated the considerable predictive prowess inherent in the included model, offering valuable insights into the incidence of acute kidney injury. This discovery, underscored by the potential for the model to evolve into an exemplary predictive tool, renders the research undeniably intriguing. However, a discerning evaluation has identified certain areas that warrant attentive refinement.
1) While the current work undeniably holds merit, its distinctive contributions and innovative implications vis-à-vis the existing corpus of literature merit greater elucidation. Enhancing the abstract and discussion sections with a more comprehensive delineation of the manuscript's novelty and its potential to pioneer novel paradigms would undoubtedly augment its scholarly impact.
2) The results section, a cornerstone of scientific exposition, could be further fortified through more elaborate descriptions of the references pertaining to the accompanying visual aids, including figures and illustrations. By providing enhanced context, these references would offer readers a more cohesive understanding of the presented findings.
3) A scrupulous commitment to linguistic precision is paramount in ensuring the coherence and professionalism of a scholarly manuscript. The discernment of numerous typographical errors and instances of incorrect punctuation impels the necessity for a thorough and meticulous review to rectify these linguistic infelicities.
In summation, the authors' diligent endeavor in conducting a systematic review and meta-analysis has unearthed captivating insights into predictive modeling for acute kidney injury. Addressing the aforementioned aspects will not only heighten the manuscript's overall impact but also amplify its potential to usher in substantive advancements within the field.
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In this intriguing study, the authors leverage the power of machine learning techniques to demonstrate a commendable level of predictive accuracy, opening avenues for a promising prospective approach in the early identification and preventive management of inflammation. The research undoubtedly holds substantial value; however, a few pivotal aspects warrant further attention.
1. While the employment of machine learning methods is commendable, it is essential to ensure clarity and accessibility for readers. To enhance the paper's comprehensibility, the authors are encouraged to spell out all abbreviations upon their first usage.
2. The scholarly rigor of the paper could be further elevated by meticulously adhering to proper referencing and formatting guidelines. The authors are advised to rectify the current discrepancy where references are neither cited nor presented in accordance with the prescribed formatting requirements.
3. The precision and consistency of data representation are paramount in bolstering the paper's credibility. It is recommended that the authors take particular care to accurately represent the 95% confidence intervals (95%CI) and maintain uniformity in their depiction throughout the manuscript.
4. In order to provide a comprehensive context to the readers, the discussion section would greatly benefit from a more robust comparative analysis of the study's findings vis-à-vis the results of prior relevant research endeavors. This comparative discourse will enable the authors to better situate their findings within the existing body of knowledge.
5. A polished and coherent writing style significantly contributes to the overall impact of a scientific paper. As such, the authors are strongly advised to subject the manuscript to meticulous English editing and correction, ensuring the text is free from grammatical errors and awkward phrasing.
In conclusion, the authors' utilization of machine learning methods to prospectively address inflammation detection and prevention is undeniably promising. Addressing the aforementioned points will not only augment the clarity and scholarly rigor of the paper but also enhance its potential contribution to the field.
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