Zobrazeno 1 - 10 of 25 pro vyhledávání: '"Marta Skreta"'
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Akademický článek
The Hydronephrosis Severity Index guides paediatric antenatal hydronephrosis management based on artificial intelligence applied to ultrasound images alone
Autor: Lauren Erdman, Mandy Rickard, Erik Drysdale, Marta Skreta, Stanley Bryan Hua, Kunj Sheth, Daniel Alvarez, Kyla N. Velaer, Michael E. Chua, Joana Dos Santos, Daniel Keefe, Norman D. Rosenblum, Megan A. Bonnett, John Weaver, Alice Xiang, Yong Fan, Bernarda Viteri, Christopher S. Cooper, Gregory E. Tasian, Armando J. Lorenzo, Anna Goldenberg
Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Antenatal hydronephrosis (HN) impacts up to 5% of pregnancies and requires close, frequent follow-up monitoring to determine who may benefit from surgical intervention. To create an automated HN Severity Index (HSI) that helps guide clinical
Externí odkaz: https://doaj.org/article/8aa35c14841242259eba98cfaf0f7df3
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3
Akademický článek
PhenoPad: Building AI enabled note-taking interfaces for patient encounters
Autor: Jixuan Wang, Jingbo Yang, Haochi Zhang, Helen Lu, Marta Skreta, Mia Husić, Aryan Arbabi, Nicole Sultanum, Michael Brudno
Publikováno v: npj Digital Medicine, Vol 5, Iss 1, Pp 1-9 (2022)
Abstract Current clinical note-taking approaches cannot capture the entirety of information available from patient encounters and detract from patient-clinician interactions. By surveying healthcare providers’ current note-taking practices and atti
Externí odkaz: https://doaj.org/article/9c638992fbb3407c9cbc21ef9baa6a1a
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4
Akademický článek
Automatically disambiguating medical acronyms with ontology-aware deep learning
Autor: Marta Skreta, Aryan Arbabi, Jixuan Wang, Erik Drysdale, Jacob Kelly, Devin Singh, Michael Brudno
Publikováno v: Nature Communications, Vol 12, Iss 1, Pp 1-10 (2021)
Disambiguating abbreviations is important for automated clinical note processing; however, deploying machine learning for this task is restricted by lack of good training data. Here, the authors show novel data augmentation methods that use biomedica
Externí odkaz: https://doaj.org/article/55b59136062549e789f34c5a3fb40092
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5
Akademický článek
The silent trial - the bridge between bench-to-bedside clinical AI applications
Autor: Jethro C. C. Kwong, Lauren Erdman, Adree Khondker, Marta Skreta, Anna Goldenberg, Melissa D. McCradden, Armando J. Lorenzo, Mandy Rickard
Publikováno v: Frontiers in Digital Health, Vol 4 (2022)
As more artificial intelligence (AI) applications are integrated into healthcare, there is an urgent need for standardization and quality-control measures to ensure a safe and successful transition of these novel tools into clinical practice. We desc
Externí odkaz: https://doaj.org/article/0a018e50dd4b46928b30848f00f881e6
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7
Posterior Urethral Valves Outcomes Prediction (PUVOP): a machine learning tool to predict clinically relevant outcomes in boys with posterior urethral valves
Autor: Neeta D'Souza, Jethro C.C. Kwong, Marta Skreta, Dana A. Weiss, Joana Dos Santos, Antoine Fermin Selman, Armando J. Lorenzo, Michael Chua, Gregory E. Tasian, Daniel T. Keefe, Adree Khondker, Lauren Erdman, Chia Wei Teoh, Christopher J. Long, John Weaver, Mandy Rickard, Jin Kyu Kim
Publikováno v: Pediatric Nephrology. 37:1067-1074
Early kidney and anatomic features may be predictive of future progression and need for additional procedures in patients with posterior urethral valve (PUV). The objective of this study was to use machine learning (ML) to predict clinically relevant
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ef846e64ff15f1146e26eb1687e14934
https://doi.org/10.1007/s00467-021-05321-3
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8
Multi-institutional Validation of Improved Vesicoureteral Reflux Assessment With Simple and Machine Learning Approaches
Autor: Adree Khondker, Jethro C. C. Kwong, Priyank Yadav, Justin Y. H. Chan, Anuradha Singh, Marta Skreta, Lauren Erdman, Daniel T. Keefe, Katherine Fischer, Gregory Tasian, Jessica H. Hannick, Frank Papanikolaou, Benjamin J. Cooper, Christopher S. Cooper, Mandy Rickard, Armando J. Lorenzo
Publikováno v: The Journal of urology. 208(6)
Vesicoureteral reflux grading from voiding cystourethrograms is highly subjective with low reliability. We aimed to demonstrate improved reliability for vesicoureteral reflux grading with simple and machine learning approaches using ureteral tortuosi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ced556b2d7e15aaa8f443a1513d0fb96
https://pubmed.ncbi.nlm.nih.gov/36349912
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9
Predictive accuracy of prenatal ultrasound findings for lower urinary tract obstruction: A systematic review and Bayesian meta‐analysis
Autor: Jin Kyu Kim, Lauren Erdman, Marta Skreta, Tim Van Mieghem, Michael Chua, Marisol Lolas, John Weaver, Gregory E. Tasian, Antoine Selman Fermin, Joana Dos Santos, Daniel T. Keefe, Mandy Rickard, Armando J. Lorenzo, Eric Mackay, Priyank Yadav
Publikováno v: Prenatal Diagnosis. 41:1039-1048
BACKGROUND Lower urinary tract obstruction (LUTO) is a rare but critical fetal diagnosis. Different ultrasound markers have been reported with varying sensitivity and specificity. AIMS The objective of this systematic review and meta-analysis was to
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7468e15469918d56350431ef40827b1c
https://doi.org/10.1002/pd.6025
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Plný text Recenzováno Digitální knihovna AV ČR
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