Evidence map›Paper›PMID 38227177›Full record

ReviewCurrent osteoporosis reports2024

The Use of Artificial Intelligence in Writing Scientific Review Articles.

Melissa A Kacena, Lilian I Plotkin, Jill C Fehrenbacher

Open access · hybridAbstract readReview
In one paragraph

Review in Current osteoporosis reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 1 pooled it
17.7field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

47 citing papers in PubMed, 1 synthesis or guideline pooled it, 147 citations in OpenAlex.

  1. Pooled it
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  5. Review
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  16. Using Artificial Intelligence for Scholarly Writing.The American journal of nursing · 2025
    Article
  17. Article
  18. Exploring AI use policies in manuscript writing in cardiology and vascular journals.American heart journal plus : cardiology research and practice · 2025
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Melissa A KacenaDepartment of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis, IN, 46202, USA. mkacena@iupui.edu.
Lilian I PlotkinDepartment of Anatomy, Cell Biology & Physiology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
Jill C FehrenbacherIndiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, 46202, USA. jfehrenb@iu.edu.
Indiana University – Purdue University Indianapolis · USRichard L. Roudebush VA Medical Center · US

Funding

Quality Assurance and Quality Control Project Management: Improving Submissions and Study Conduct in the Human Subjects Research Prior Approval ProcessUL1TR002529 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI MOE, SHARON M, WIEHE, SARAH ELIZABETH · 2018 to 2022
$27.2M
Angiogenic Therapy: Novel Approaches to Enhance Bone Regeneration in Aging - LOADR01AG060621 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI KACENA, MELISSA A, LI, JILIANG · 2019 to 2023
$3.7M
Contribution of chromosome versus gonadal sex to bone mass and strengthR21AG078861 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI PLOTKIN, LILIAN IRENE · 2022 to 2023
$832k
Impact of TPO Treatment on Bone Healing and Angiogenesis in Type 2 DiabetesI01BX003751 · VA · RLR VA MEDICAL CENTER · PI KACENA, MELISSA A · 2017 to 2021
–
RR&D Research Career Scientist Award ApplicationIK6RX004809 · VA · RLR VA MEDICAL CENTER · PI KACENA, MELISSA A · 2023 to 2025
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Skeletal complications to a TREM2 variant associated with Alzheimer's DiseaseI01BX005154 · VA · RLR VA MEDICAL CENTER · PI PLOTKIN, LILIAN IRENE · 2021 to 2024
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"Novel therapeutic approaches to improve fracture healing while reducing pain behavior"I01RX003552 · VA · RLR VA MEDICAL CENTER · PI KACENA, MELISSA A · 2022 to 2025
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BLRD VA I01 BX003751BLRD VA I01 BX005154BLRD VA I01 BX006399NCATS NIH HHS UL1 TR002529NIA NIH HHS R01 AG060621NIA NIH HHS R21 AG078861NIH HHS AG060621/AG060621-05S1/AG060621-05S2NIH HHS AG078861/AG078861-S1RRD VA I01 RX003552RRD VA IK6 RX004809
6 · The paper itself

Abstract

purpose of reviewWith the recent explosion in the use of artificial intelligence (AI) and specifically ChatGPT, we sought to determine whether ChatGPT could be used to assist in writing credible, peer-reviewed, scientific review articles. We also sought to assess, in a scientific study, the advantages and limitations of using ChatGPT for this purpose. To accomplish this, 3 topics of importance in musculoskeletal research were selected: (1) the intersection of Alzheimer's disease and bone; (2) the neural regulation of fracture healing; and (3) COVID-19 and musculoskeletal health. For each of these topics, 3 approaches to write manuscript drafts were undertaken: (1) human only; (2) ChatGPT only (AI-only); and (3) combination approach of #1 and #2 (AI-assisted). Articles were extensively fact checked and edited to ensure scientific quality, resulting in final manuscripts that were significantly different from the original drafts. Numerous parameters were measured throughout the process to quantitate advantages and disadvantages of approaches. RECENT

findingsOverall, use of AI decreased the time spent to write the review article, but required more extensive fact checking. With the AI-only approach, up to 70% of the references cited were found to be inaccurate. Interestingly, the AI-assisted approach resulted in the highest similarity indices suggesting a higher likelihood of plagiarism. Finally, although the technology is rapidly changing, at the time of study, ChatGPT 4.0 had a cutoff date of September 2021 rendering identification of recent articles impossible. Therefore, all literature published past the cutoff date was manually provided to ChatGPT, rendering approaches #2 and #3 identical for contemporary citations. As a result, for the COVID-19 and musculoskeletal health topic, approach #2 was abandoned midstream due to the extensive overlap with approach #3. The main objective of this scientific study was to see whether AI could be used in a scientifically appropriate manner to improve the scientific writing process. Indeed, AI reduced the time for writing but had significant inaccuracies. The latter necessitates that AI cannot currently be used alone but could be used with careful oversight by humans to assist in writing scientific review articles.

Indexed as

Artificial IntelligenceCOVID-19Fracture HealingHumansWritingAlzheimer's diseaseArtificial intelligence (AI)ChatGPTCOVID-19Fracture healingMusculoskeletal systemNeural regulationOsteoporosisSARS-CoV-2Scientific writing

Identifiers

PMID38227177
PMCPMC10912250
OpenAlexW4390904004

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.