AI aided analysis on saliva crystallization of pregnant women for accurate estimation of delivery date and fetal status.

医学 产科 怀孕 唾液
作者
Zhou-Xuan Li,Yue-Ming Zha,Guang-Yun Jiang,Yao-Xiong Huang
出处
期刊:IEEE Journal of Biomedical and Health Informatics [Institute of Electrical and Electronics Engineers]
卷期号:PP
标识
DOI:10.1109/jbhi.2021.3135534
摘要

Saliva contains similar molecular components to serum. Analysis of saliva can provide important diagnostic information about the body. Here we report an artificial intelligence (AI) aided home-based method that can let pregnant women perform daily monitoring on their pregnant status and accurate prediction on their delivery date by the pattern analysis of their salivary crystals. The method was developed based on the information obtained from our investigation on the saliva samples of 170 pregnant women about the correlation of the salivary crystal pattern with pregnant age and fetal status. It demonstrated that the patterns of salivary crystallization could act as indicators of the pregnant age, fetal state, and some medical conditions of pregnant women. On this basis, with the aid of AI recognition and analysis of the fractal dimension and some characteristic crystals in the salivary crystallization, we performed estimation on the delivery date in both quantitative and qualitative manners. The accuracy of the prediction on 15 pregnant women was satisfactory: 100 % delivering in the predicted week, 93.3 % within the estimated three days, and 86.7 % on the day as the prediction. We also developed a simple smartphone-based AI-aided salivary crystal imaging and analysis device as an auxiliary means to let pregnant women monitor their fetal status daily at home and predict their delivery date with adequate accuracy.
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
k123456应助huco采纳,获得10
刚刚
orixero应助huco采纳,获得10
刚刚
共享精神应助huco采纳,获得10
刚刚
搜集达人应助huco采纳,获得10
1秒前
TanFT发布了新的文献求助10
1秒前
Frank应助雷寒云采纳,获得10
3秒前
4秒前
zhangpeng完成签到,获得积分10
4秒前
淡定沧海完成签到,获得积分10
5秒前
5秒前
6秒前
7秒前
天天快乐应助姜丝罐罐n采纳,获得10
7秒前
ddd完成签到,获得积分10
8秒前
8秒前
旺仔完成签到,获得积分10
8秒前
candyTT完成签到,获得积分10
9秒前
李爱国应助TanFT采纳,获得10
9秒前
ggghh发布了新的文献求助30
11秒前
丁驰发布了新的文献求助18
11秒前
12秒前
banana95发布了新的文献求助10
13秒前
冷漠的布丁完成签到,获得积分10
16秒前
共享精神应助阳光沛柔采纳,获得10
16秒前
成就的水之完成签到,获得积分10
17秒前
科研八戒发布了新的文献求助10
17秒前
量子星尘发布了新的文献求助10
18秒前
mmain完成签到 ,获得积分10
19秒前
水水完成签到,获得积分10
19秒前
科研用户N完成签到 ,获得积分10
21秒前
月光族完成签到,获得积分10
21秒前
情怀应助对方正在输入中采纳,获得10
22秒前
23秒前
23秒前
情怀应助欢呼的小玉采纳,获得10
26秒前
27秒前
27秒前
27秒前
27秒前
小零发布了新的文献求助10
29秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Alloy Phase Diagrams 1000
Introduction to Early Childhood Education 1000
2025-2031年中国兽用抗生素行业发展深度调研与未来趋势报告 1000
List of 1,091 Public Pension Profiles by Region 901
Item Response Theory 600
Historical Dictionary of British Intelligence (2014 / 2nd EDITION!) 500
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 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5425362
求助须知:如何正确求助?哪些是违规求助? 4539459
关于积分的说明 14168091
捐赠科研通 4456964
什么是DOI,文献DOI怎么找? 2444356
邀请新用户注册赠送积分活动 1435316
关于科研通互助平台的介绍 1412740