Precision at its Core: Machine Learning-Infused Metabolomics Model for Preterm Birth Prediction in Human-Reference-Cited by-同舟云学术

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Precision at its Core: Machine Learning-Infused Metabolomics Model for Preterm Birth Prediction in Human

Published:2023-07-06 Issue: Volume: Page:
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Container-title:2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
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Author:

Tandon Ansh¹,Gupta Tushar¹,Verma Aysha¹,Kulshrestha Sudeepti¹,Dua Riya¹,Varghese Sharvin¹,Gupta Romasha¹,Abbasi Nagma²,Narad Priyanka¹,Chaurasia Ankur³,Sengupta Abhishek¹

Affiliation:

1. Amity University,Systems Biology Data Analytics Lab Amity Institute of Biotechnology,Noida,Uttar Pradesh,India

2. NextGen Life Sciences Pvt. Ltd.,Delhi,India

3. Amity University,Amity Institute of Biotechnology,Noida,Uttar Pradesh,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10306338/10306339/10307581.pdf?arnumber=10307581

Reference32 articles.

1. Cervical Length Changes From the First to Second Trimester of Pregnancy, and Prediction of Preterm Birth by First-Trimester Sonographic Cervical Measurement

2. First-Trimester Screening for Spontaneous Preterm Delivery with Maternal Characteristics and Cervical Length

3. Cervicovaginal microbiota and metabolome predict preterm birth risk in an ethnically diverse cohort

4. Cervicovaginal fetal fibronectin for the prediction of spontaneous preterm birth in multiple pregnancies: a systematic review and meta-analysis

5. Maternal socioeconomic factors and the risk of premature birth and low birth weight in Cyprus: a case–control study

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