Artificial Intelligence for Emerging Technology in Surgery: Systematic Review and Validation
| العنوان: | Artificial Intelligence for Emerging Technology in Surgery: Systematic Review and Validation |
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| المؤلفون: | Ephraim Nwoye, Wai Lok Woo, Bin Gao, Tobenna Anyanwu |
| المصدر: | IEEE Reviews in Biomedical Engineering. 16:241-259 |
| بيانات النشر: | Institute of Electrical and Electronics Engineers (IEEE), 2023. |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Biomedical Engineering, G900, G700, B800 |
| الوصف: | Surgery is a high-risk procedure of therapy and is associated to post trauma complications of longer hospital stay, estimated blood loss and long duration of surgeries. Reports have suggested that over 2.5% patients die during and post operation. This paper is aimed at systematic review of previous research on artificial intelligence (AI) in surgery, analyzing their results with suitable software to validate their research by obtaining same or contrary results. Six published research articles have been reviewed across three continents. These articles have been re-validated using software including SPSS and MedCalc to obtain the statistical features such as the mean, standard deviation, significant level, and standard error. From the significant values, the experiments are then classified according to the null (p0.05) hypotheses. The results obtained from the analysis have suggested significant difference in operating time, docking time, staging time, and estimated blood loss but show no significant difference in length of hospital stay, recovery time and lymph nodes harvested between robotic assisted surgery using AI and normal conventional surgery. From the evaluations, this research suggests that AI-assisted surgery improves over the conventional surgery as safer and more efficient system of surgery with minimal or no complications. |
| وصف الملف: | application/pdf |
| تدمد: | 1941-1189 1937-3333 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c2433c11994c20a4753e5d416d086680 https://doi.org/10.1109/rbme.2022.3183852 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....c2433c11994c20a4753e5d416d086680 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 19411189 19373333 |
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