Evelina London Children's Healthcare

Three-dimensional printed models for surgical planning of complex congenital heart defects: an international multicentre study

Israel Valverde, Gorka Gómez, Tarique Hussain et al.

2017 · 270 Zit.

Artificial intelligence, fetal echocardiography, and congenital heart disease

Thomas G. Day, Bernhard Kainz, Joseph V. Hajnal et al.

2021 · 51 Zit.

Criss‐cross heart three‐dimensional printed models in medical education: A multicenter study on their value as a supporting tool to conventional imaging

Israel Valverde, Gorka Gómez, Nick Byrne et al.

2021 · 32 Zit.

Interaction between clinicians and artificial intelligence to detect fetal atrioventricular septal defects on ultrasound: how can we optimize collaborative performance?

Thomas G. Day, Jacqueline Matthew, Samuel Budd et al.

2024 · 13 Zit.

Artificial intelligence (AI) in radiological paediatric fracture assessment: an updated systematic review

Emily Ashworth, Emma Allan, Cato Pauling et al.

2025 · 9 Zit.

Sonographer interaction with artificial intelligence: collaboration or conflict?

Thomas G. Day, Jacqueline Matthew, S. Budd et al.

2023 · 5 Zit.

Video Clip Extraction From Fetal Ultrasound Scans Using Artificial Intelligence to Allow Remote Second Expert Review for Congenital Heart Disease

Thomas G. Day, Lorenzo Venturini, Samuel Budd et al.

2025 · 3 Zit.

Improving image labelling quality

Thomas G. Day, John Simpson, Reza Razavi et al.

2023 · 3 Zit.

AI to Assist in the Fetal Anomaly Ultrasound Scan: A Randomized Controlled Trial

Thomas G. Day, Jacqueline Matthew, Samuel Budd et al.

2025 · 2 Zit.

Exploring AI: Transforming medical practice, education and research

Bernhard Haid, Caleb P. Nelson, Muhammet İrfan Dönmez et al.

2024 · 0 Zit.

122 Predicting progression of paediatric Chronic Kidney Disease using Machine Learning

Aliea Mahmood, Mandy Wan, Victoria Stevens et al.

2026 · 0 Zit.