AI Article Synopsis
- The study aimed to compare the accuracy of open-source AI language models against human authors in generating a systematic review on pulsed-Thulium:YAG laser.
- Five manuscripts were assessed by both independent certified endourologists and four different AI models, with the human review serving as the benchmark for accuracy.
- Results indicated that while human-generated content was significantly more accurate than AI outputs, ChatGPT3.5 performed the best among the AI models, suggesting that AI can be useful with human oversight in technical fields.
Article Abstract
Purpose: To compare the accuracy of open-source Artificial Intelligence (AI) Large Language Models (LLM) against human authors to generate a systematic review (SR) on the new pulsed-Thulium:YAG (p-Tm:YAG) laser.
Methods: Five manuscripts were compared. The Human-SR on p-Tm:YAG (considered to be the "ground truth") was written by independent certified endourologists with expertise in lasers, accepted in a peer-review pubmed-indexed journal (but not yet available online, and therefore not accessible to the LLMs). The query to the AI LLMs was: "write a systematic review on pulsed-Thulium:YAG laser for lithotripsy" which was submitted to four LLMs (ChatGPT3.5/Vercel/Claude/Mistral-7b). The LLM-SR were uniformed and Human-SR reformatted to fit the general output appearance, to ensure blindness. Nine participants with various levels of endourological expertise (three Clinical Nurse Specialist nurses, Urology Trainees and Consultants) objectively assessed the accuracy of the five SRs using a bespoke 10 "checkpoint" proforma. A subjective assessment was recorded using a composite score including quality (0-10), clarity (0-10) and overall manuscript rank (1-5).
Results: The Human-SR was objectively and subjectively more accurate than LLM-SRs (96 ± 7% and 86.8 ± 8.2% respectively; p < 0.001). The LLM-SRs did not significantly differ but ChatGPT3.5 presented greater subjective and objective accuracy scores (62.4 ± 15% and 29 ± 28% respectively; p > 0.05). Quality and clarity assessments were significantly impacted by SR type but not the expertise level (p < 0.001 and > 0.05, respectively).
Conclusions: LLM generated data on highly technical topics present a lower accuracy than Key Opinion Leaders. LLMs, especially ChatGPT3.5, with human supervision could improve our practice.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/s00345-024-05311-8 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Estimation of Central Aortic Pressure Waveforms by Combination of a Meta-Learning Neural Network and a Physics-Driven Method.
Int J Numer Method Biomed Eng
January 2025
College of Chemistry and Life Science, Beijing University of Technology, Beijing, China.
The accurate non-invasive detection and estimation of central aortic pressure waveforms (CAPW) are crucial for reliable treatments of cardiovascular system diseases. But the accuracy and practicality of current estimation methods need to be improved. Our study combines a meta-learning neural network and a physics-driven method to accurately estimate CAPW based on personalized physiological indicators.
View Article and Find Full Text PDFFully 3D-Printed Soft Capacitive Sensor of High Toughness and Large Measurement Range.
Adv Sci (Weinh)
January 2025
School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, 518172, P. R. China.
Soft capacitive sensors are widely utilized in wearable devices, flexible electronics, and soft robotics due to their high sensitivity. However, they may suffer delamination and/or debonding due to their low interfacial toughness. In addition, they usually exhibit a small measurement range resulting from their limited stiffness variation range.
View Article and Find Full Text PDFIncidence of fall-from-height injuries and predictive factors for severity.
J Osteopath Med
January 2025
McAllen Department of Trauma, South Texas Health System, McAllen, TX, USA.
Context: The injuries caused by falls-from-height (FFH) are a significant public health concern. FFH is one of the most common causes of polytrauma. The injuries persist to be significant adverse events and a challenge regarding injury severity assessment to identify patients at high risk upon admission.
View Article and Find Full Text PDFA Soft Robotic Sleeve for Physiotherapy: Improving Elbow Rehabilitation in Baseball Pitchers.
Physiother Res Int
January 2025
Department of Biomedical Engineering, University of Engineering and Technology (UET) Lahore, Narowal Campus, Narowal, Pakistan.
Background And Purpose: Throwing a baseball involves intense exposure of the arm to high speeds and powerful forces, which contributes to an increasing prevalence of arm injuries among athletes. Traditional rigid exoskeletons and rehabilitation equipment frequently lack portability, safety, ergonomic design, and affordability. Traditional rehabilitation approaches frequently require therapist monitoring, resulting in therapy delays.
View Article and Find Full Text PDFSTMGraph: spatial-context-aware of transcriptomes via a dual-remasked dynamic graph attention model.
Brief Bioinform
November 2024
Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, No. 15 Shangxiadian Road, Cangshan District, Fuzhou 350002, China.
Spatial transcriptomics (ST) technologies enable dissecting the tissue architecture in spatial context. To perceive the global contextual information of gene expression patterns in tissue, the spatial dependence of cells must be fully considered by integrating both local and non-local features by means of spatial-context-aware. However, the current ST integration algorithm ignores for ST dropouts, which impedes the spatial-aware of ST features, resulting in challenges in the accuracy and robustness of microenvironmental heterogeneity detecting, spatial domain clustering, and batch-effects correction.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!