相关实验视频

Updated: Jan 16, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

800

基于卷积神经网络的AI在检测口腔状细胞癌的诊断性能:元分析

Mi Shen1, Zhili Jiang1,2, Yankun Feng1

  • 1School of Stomatology, Hunan University of Chinese Medicine, Changsha, Hunan, 410006, China.

BMC oral health
|January 15, 2026
PubMed
概括

基于卷积神经网络 (CNN) 的人工智能 (AI) 在诊断口腔状细胞癌 (OSCC) 中显示出高准确性. 需要进一步的前性研究来将这种AI工具整合到常规的临床实践中,以改善口腔癌的检测.

关键词:
人工智能的人工智能是人工智能.卷积神经网络是一种卷积神经网络.诊断 诊断 诊断 诊断 诊断进行元分析分析.口腔状细胞癌的癌症.

更多相关视频

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

489
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

7.4K

相关概念视频

Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
471