The Role of Artificial Intelligence Combined With Digital Cholangioscopy for Indeterminant and Malignant Biliary Strictures

医学 诊断优势比 内镜逆行胰胆管造影术 荟萃分析 接收机工作特性 诊断准确性 人工智能 放射科 内科学 计算机科学 胰腺炎
作者
Thomas R. McCarty,Raj J. Shah,Ronan Allencherril,Nabeel Moon,Basile Njei
出处
期刊:Journal of Clinical Gastroenterology [Lippincott Williams & Wilkins]
标识
DOI:10.1097/mcg.0000000000002148
摘要

Background: Current endoscopic retrograde cholangiopancreatography (ERCP) and cholangioscopic-based diagnostic sampling for indeterminant biliary strictures remain suboptimal. Artificial intelligence (AI)-based algorithms by means of computer vision in machine learning have been applied to cholangioscopy in an effort to improve diagnostic yield. The aim of this study was to perform a systematic review and meta-analysis to evaluate the diagnostic performance of AI-based diagnostic performance of AI-associated cholangioscopic diagnosis of indeterminant or malignant biliary strictures. Methods: Individualized searches were developed in accordance with PRISMA and MOOSE guidelines, and meta-analysis according to Cochrane Diagnostic Test Accuracy working group methodology. A bivariate model was used to compute pooled sensitivity and specificity, likelihood ratio, diagnostic odds ratio, and summary receiver operating characteristics curve (SROC). Results: Five studies (n=675 lesions; a total of 2,685,674 cholangioscopic images) were included. All but one study analyzed a deep learning AI-based system using a convoluted neural network (CNN) with an average image processing speed of 30 to 60 frames per second. The pooled sensitivity and specificity were 95% (95% CI: 85-98) and 88% (95% CI: 76-94), with a diagnostic accuracy (SROC) of 97% (95% CI: 95-98). Sensitivity analysis of CNN studies (4 studies, 538 patients) demonstrated a pooled sensitivity, specificity, and accuracy (SROC) of 95% (95% CI: 82-99), 88% (95% CI: 72-95), and 97% (95% CI: 95-98), respectively. Conclusions: Artificial intelligence-based machine learning of cholangioscopy images appears to be a promising modality for the diagnosis of indeterminant and malignant biliary strictures.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
852应助33采纳,获得30
刚刚
zyw完成签到,获得积分10
1秒前
勤劳的白开水完成签到,获得积分10
2秒前
Blue发布了新的文献求助10
2秒前
大模型应助欧阳月空采纳,获得10
6秒前
6秒前
ElvisWu完成签到,获得积分10
7秒前
7秒前
9秒前
moji发布了新的文献求助10
10秒前
Imp完成签到,获得积分10
12秒前
12秒前
13秒前
量子星尘发布了新的文献求助10
13秒前
14秒前
33发布了新的文献求助30
14秒前
彦卿完成签到 ,获得积分10
15秒前
思源应助赵清持采纳,获得10
16秒前
张雯思发布了新的文献求助10
17秒前
Orange应助Shrine采纳,获得10
18秒前
19秒前
卡卡罗特发布了新的文献求助10
19秒前
cdytjt完成签到,获得积分10
21秒前
24秒前
ding应助小田心采纳,获得10
24秒前
24秒前
24秒前
25秒前
25秒前
wwl发布了新的文献求助10
26秒前
鹏程万里完成签到,获得积分10
27秒前
星辰大海应助li采纳,获得10
28秒前
chasikan发布了新的文献求助30
29秒前
cxy发布了新的文献求助10
30秒前
幸福大白发布了新的文献求助10
31秒前
大个应助贾克斯采纳,获得10
33秒前
过时的画板完成签到,获得积分10
33秒前
大气小蘑菇完成签到,获得积分10
36秒前
37秒前
小田心发布了新的文献求助10
43秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
‘Unruly’ Children: Historical Fieldnotes and Learning Morality in a Taiwan Village (New Departures in Anthropology) 400
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 350
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3989406
求助须知:如何正确求助?哪些是违规求助? 3531522
关于积分的说明 11254187
捐赠科研通 3270174
什么是DOI,文献DOI怎么找? 1804901
邀请新用户注册赠送积分活动 882105
科研通“疑难数据库(出版商)”最低求助积分说明 809174