Work

VP17.01: Exploring a new paradigm for the fetal anomaly ultrasound scan: artificial intelligence in real‐time

Year: 2021

Type: conference-abstract

Source: Ultrasound in Obstetrics and Gynecology

DOI: 10.1002/uog.24290

Authors: J. Matthew, E. Skelton, T. Day, V. Zimmer, A. Gomez, G. Wheeler, N. Toussaint, T. Liu, S. Budd, K. Lloyd, R. Wright, S. Deng, N. Ghavami, M. Sinclair, Q. Meng, B. Kainz, J. Schnabel, D. Rueckert, R. Razavi, J. Simpson, J. Hajnal

Institutions: King's College London, Guy's and St Thomas' NHS Foundation Trust, Imperial College London, Technical University of Munich

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W3207780930

Cites:

Cited by: 1

Related to: 10