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For: Gil MM, Cuenca-Gómez D, Rolle V, Pertegal M, Díaz C, Revello R, Adiego B, Mendoza M, Molina FS, Santacruz B, Ansbacher-Feldman Z, Meiri H, Martin-Alonso R, Louzoun Y, De Paco Matallana C. Validation of machine-learning model for first-trimester prediction of pre-eclampsia using cohort from PREVAL study. Ultrasound Obstet Gynecol 2024;63:68-74. [PMID: 37698356 DOI: 10.1002/uog.27478] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 07/28/2023] [Accepted: 08/15/2023] [Indexed: 09/13/2023]
Number Cited by Other Article(s)
1
Giaxi P, Vivilaki V, Sarella A, Harizopoulou V, Gourounti K. Artificial Intelligence and Machine Learning: An Updated Systematic Review of Their Role in Obstetrics and Midwifery. Cureus 2025;17:e80394. [PMID: 40070886 PMCID: PMC11895402 DOI: 10.7759/cureus.80394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/11/2025] [Indexed: 03/14/2025]  Open
2
Malik V, Agrawal N, Prasad S, Talwar S, Khatuja R, Jain S, Sehgal NP, Malik N, Khatuja J, Madan N. Prediction of Preeclampsia Using Machine Learning: A Systematic Review. Cureus 2024;16:e76095. [PMID: 39834976 PMCID: PMC11743919 DOI: 10.7759/cureus.76095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/20/2024] [Indexed: 01/22/2025]  Open
3
Feng W, Luo Y. Preeclampsia and its prediction: traditional versus contemporary predictive methods. J Matern Fetal Neonatal Med 2024;37:2388171. [PMID: 39107137 DOI: 10.1080/14767058.2024.2388171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Revised: 07/29/2024] [Accepted: 07/30/2024] [Indexed: 08/09/2024]
4
Nguyen-Hoang L, Sahota DS, Pooh RK, Duan H, Chaiyasit N, Sekizawa A, Shaw SW, Seshadri S, Choolani M, Yapan P, Sim WS, Ma R, Leung WC, Lau SL, Lee NMW, Leung HYH, Meshali T, Meiri H, Louzoun Y, Poon LC. Validation of the first-trimester machine learning model for predicting pre-eclampsia in an Asian population. Int J Gynaecol Obstet 2024;167:350-359. [PMID: 38666305 DOI: 10.1002/ijgo.15563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 04/07/2024] [Accepted: 04/16/2024] [Indexed: 09/25/2024]
5
Ricci CA, Crysup B, Phillips NR, Ray WC, Santillan MK, Trask AJ, Woerner AE, Goulopoulou S. Machine learning: a new era for cardiovascular pregnancy physiology and cardio-obstetrics research. Am J Physiol Heart Circ Physiol 2024;327:H417-H432. [PMID: 38847756 PMCID: PMC11442027 DOI: 10.1152/ajpheart.00149.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 05/31/2024] [Accepted: 05/31/2024] [Indexed: 06/10/2024]
6
Drukker L. The Holy Grail of obstetric ultrasound: can artificial intelligence detect hard-to-identify fetal cardiac anomalies? ULTRASOUND IN OBSTETRICS & GYNECOLOGY : THE OFFICIAL JOURNAL OF THE INTERNATIONAL SOCIETY OF ULTRASOUND IN OBSTETRICS AND GYNECOLOGY 2024;64:5-9. [PMID: 38949769 DOI: 10.1002/uog.27703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 04/18/2024] [Indexed: 07/02/2024]
7
Li T, Xu M, Wang Y, Wang Y, Tang H, Duan H, Zhao G, Zheng M, Hu Y. Prediction model of preeclampsia using machine learning based methods: a population based cohort study in China. Front Endocrinol (Lausanne) 2024;15:1345573. [PMID: 38919479 PMCID: PMC11198873 DOI: 10.3389/fendo.2024.1345573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 05/27/2024] [Indexed: 06/27/2024]  Open
8
Shara N, Mirabal-Beltran R, Talmadge B, Falah N, Ahmad M, Dempers R, Crovatt S, Eisenberg S, Anderson K. Use of Machine Learning for Early Detection of Maternal Cardiovascular Conditions: Retrospective Study Using Electronic Health Record Data. JMIR Cardio 2024;8:e53091. [PMID: 38648629 DOI: 10.2196/53091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 03/08/2024] [Accepted: 03/11/2024] [Indexed: 04/25/2024]  Open
9
Xia Y, Wang Y, Yuan S, Hu J, Zhang L, Xie J, Zhao Y, Hao J, Ren Y, Wu S. Development and validation of nomograms to predict clinical outcomes of preeclampsia. Front Endocrinol (Lausanne) 2024;15:1292458. [PMID: 38549768 PMCID: PMC10972945 DOI: 10.3389/fendo.2024.1292458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 02/14/2024] [Indexed: 04/02/2024]  Open
10
Vasilache IA, Scripcariu IS, Doroftei B, Bernad RL, Cărăuleanu A, Socolov D, Melinte-Popescu AS, Vicoveanu P, Harabor V, Mihalceanu E, Melinte-Popescu M, Harabor A, Bernad E, Nemescu D. Prediction of Intrauterine Growth Restriction and Preeclampsia Using Machine Learning-Based Algorithms: A Prospective Study. Diagnostics (Basel) 2024;14:453. [PMID: 38396491 PMCID: PMC10887724 DOI: 10.3390/diagnostics14040453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 02/10/2024] [Accepted: 02/16/2024] [Indexed: 02/25/2024]  Open
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