D. Coronado-Gutiérrez

Concordance of the risk of neonatal respiratory morbidity assessed by quantitative ultrasound lung texture analysis in fetuses of twin pregnancies

X. Burgos-Artizzu, E. Gratacós, M. Palacio, 2022, Scientific reports.

The Association Between Early Membrane Rupture, Latency, Clinical Chorioamnionitis, Neonatal Infection, and Adverse Perinatal Outcomes in Twin Pregnancies Complicated by Preterm Prelabour Rupture of Membranes

M. Palacio, L. Trigo, D. Lip-Sosa, 2003, Twin Research.

Evaluation of deep convolutional neural networks for automatic classification of common maternal fetal ultrasound planes

Xavier P. Burgos-Artizzu, Brenda Valenzuela-Alcaraz, Eduard Gratacós, 2020, Scientific Reports.

Concordance of the risk of neonatal respiratory morbidity assessed by quantitative ultrasound lung texture analysis in fetuses of twin pregnancies

X. Burgos-Artizzu, E. Gratacós, M. Palacio, 2022, Scientific Reports.

Evaluation of an improved tool for non-invasive prediction of neonatal respiratory morbidity based on fully automated fetal lung ultrasound analysis

Xavier P. Burgos-Artizzu, Eduard Gratacos, Montse Palacio, 2019, Scientific Reports.

Skin cancer high-risk patient screening from dermoscopic images via Artificial Intelligence: an online study

X. Burgos-Artizzu, D. Coronado-Gutiérrez, C. López, 2021, medRxiv.

Intra- and interobserver reproducibility of second trimester ultrasound cervical length measurement in a general population

X. Burgos-Artizzu, E. Gratacós, A. Perez-Moreno, 2020, The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians.

Quantitative Ultrasound Image Analysis of Axillary Lymph Nodes to Diagnose Metastatic Involvement in Breast Cancer.

Xavier P. Burgos-Artizzu, Xavier Bargalló, Sergi Ganau, 2019, Ultrasound in medicine & biology.

Quantitative ultrasound image analysis of axillary lymph nodes to differentiate malignancy from reactive benign changes due to COVID-19 vaccination

X. Burgos-Artizzu, X. Bargalló, S. Ganau, 2022, European Journal of Radiology.

Glaucoma patient screening from online retinal fundus images via Artificial Intelligence

X. Burgos-Artizzu, D. Coronado-Gutiérrez, P. Franco, 2021, medRxiv.

Evaluation of an improved tool for non-invasive prediction of neonatal respiratory morbidity based on fully automated fetal lung ultrasound analysis

X. Burgos-Artizzu, E. Gratacós, A. Perez-Moreno, 2019, Scientific Reports.

Prediction of Neonatal Respiratory Morbidity Assessed by Quantitative Ultrasound Lung Texture Analysis in Twin Pregnancies

X. Burgos-Artizzu, E. Gratacós, M. Palacio, 2022, Journal of clinical medicine.

Mid-trimester prediction of spontaneous preterm birth with automated cervical quantitative ultrasound texture analysis and cervical length: a prospective study

X. Burgos-Artizzu, E. Gratacós, A. Perez-Moreno, 2021, Scientific Reports.

Automatic Deep Learning-Based Pipeline for Automatic Delineation and Measurement of Fetal Brain Structures in Routine Mid-Trimester Ultrasound Images

X. Burgos-Artizzu, E. Gratacós, E. Bonet-Carne, 2023, Fetal Diagnosis and Therapy.

Analysis of maturation features in fetal brain ultrasound via Artificial Intelligence for the estimation of gestational age.

X. Burgos-Artizzu, E. Gratacós, F. Crispi, 2021, American journal of obstetrics & gynecology MFM.