This paper is in the following e-collection/theme issue:

Non-randomized Protocols and Methods (ehealth) (567) Artificial Intelligence (1371) Obstetrics, Gynecology, and Reproductive Medicine (225)

Published on in Vol 11, No 9 (2022): September

This is a member publication of University of Oxford (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37374, first published .
Developing Clinical Artificial Intelligence for Obstetric Ultrasound to Improve Access in Underserved Regions: Protocol for a Computer-Assisted Low-Cost Point-of-Care UltraSound (CALOPUS) Study

Developing Clinical Artificial Intelligence for Obstetric Ultrasound to Improve Access in Underserved Regions: Protocol for a Computer-Assisted Low-Cost Point-of-Care UltraSound (CALOPUS) Study

Developing Clinical Artificial Intelligence for Obstetric Ultrasound to Improve Access in Underserved Regions: Protocol for a Computer-Assisted Low-Cost Point-of-Care UltraSound (CALOPUS) Study

Authors of this article:

Alice Self1 Author Orcid Image ;   Qingchao Chen2 Author Orcid Image ;   Bapu Koundinya Desiraju3 Author Orcid Image ;   Sumeet Dhariwal2 Author Orcid Image ;   Alexander D Gleed2 Author Orcid Image ;   Divyanshu Mishra3 Author Orcid Image ;   Ramachandran Thiruvengadam3 Author Orcid Image ;   Varun Chandramohan3 Author Orcid Image ;   Rachel Craik1 Author Orcid Image ;   Elizabeth Wilden2 Author Orcid Image ;   Ashok Khurana4 Author Orcid Image ;   The CALOPUS Study Group5 ;   Shinjini Bhatnagar3 Author Orcid Image ;   Aris T Papageorghiou1, 6 Author Orcid Image ;   J Alison Noble2 Author Orcid Image
Article Authors Cited by (11) Tweetations (2) Metrics

Journals

  1. Toscano M, Marini T, Lennon C, Erlick M, Silva H, Crofton K, Serratelli W, Rana N, Dozier A, Castaneda B, Baran T, Drennan K. Diagnosis of Pregnancy Complications Using Blind Ultrasound Sweeps Performed by Individuals Without Prior Formal Ultrasound Training. Obstetrics & Gynecology 2023 View
  2. Venkatayogi N, Gupta M, Gupta A, Nallaparaju S, Cheemalamarri N, Gilari K, Pathak S, Vishwanath K, Soney C, Bhattacharya T, Maleki N, Purkayastha S, Gichoya J. From Seeing to Knowing with Artificial Intelligence: A Scoping Review of Point-of-Care Ultrasound in Low-Resource Settings. Applied Sciences 2023;13(14):8427 View
  3. Ranger B, Bradburn E, Chen Q, Kim M, Noble J, Papageorghiou A. Portable ultrasound devices for obstetric care in resource-constrained environments: mapping the landscape. Gates Open Research 2023;7:133 View
  4. Gidlöf S. Task‐shifting from healthcare staff to patients is necessary for the future. Acta Obstetricia et Gynecologica Scandinavica 2024;103(5):784 View
  5. Gleed A, Mishra D, Self A, Thiruvengadam R, Desiraju B, Bhatnagar S, Papageorghiou A, Noble J. Statistical Characterisation of Fetal Anatomy in Simple Obstetric Ultrasound Video Sweeps. Ultrasound in Medicine & Biology 2024;50(7):985 View
  6. Huang X. Advancements in artificial intelligence for pelvic floor ultrasound analysis. American Journal of Translational Research 2024;16(4):1037 View
  7. Ranger B, Bradburn E, Chen Q, Kim M, Noble J, Papageorghiou A. Portable ultrasound devices for obstetric care in resource-constrained environments: mapping the landscape. Gates Open Research 2024;7:133 View

Books/Policy Documents

  1. Kwon J, Jiao J, Self A, Alison Noble J, Papageorghiou A. Trustworthy Machine Learning for Healthcare. View
  2. Zhao H, Men Q, Gleed A, Papageorghiou A, Noble J. Simplifying Medical Ultrasound. View
  3. Guo X, Men Q, Noble J. Medical Image Computing and Computer Assisted Intervention – MICCAI 2024. View