Machine Learning in Fetal Cardiology: What to Expect

Machine Learning in Medicine

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FUIQA: Fetal Ultrasound Image Quality Assessment with Deep Convolutional Networks

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Ultrasound‐based gestational‐age estimation in late pregnancy

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Comparison of logistic regression with machine learning methods for the prediction of fetal growth abnormalities: a retrospective cohort study

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Fetal Cardiac Function: Technical Considerations and Potential Research and Clinical Applications

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Intrapartum Electronic Fetal Heart Rate Monitoring and the Prevention of Perinatal Brain Injury

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Fetal health status prediction based on maternal clinical history using machine learning techniques

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Automatic Fetal Head Circumference Measurement in Ultrasound Using Random Forest and Fast Ellipse Fitting

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Fetal cardiovascular remodeling persists at 6 months in infants with intrauterine growth restriction: Fetal cardiovascular remodeling persists in IUGR infants

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Fetal Intelligent Navigation Echocardiography ( <scp>FINE</scp> ): a novel method for rapid, simple, and automatic examination of the fetal heart

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Automated Fetal Head Detection and Circumference Estimation from Free-Hand Ultrasound Sweeps Using Deep Learning in Resource-Limited Countries

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Use of artificial intelligence (AI) in the interpretation of intrapartum fetal heart rate (FHR) tracings: a systematic review and meta-analysis

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Persistence of Cardiac Remodeling in Preadolescents With Fetal Growth Restriction

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Omniview-SisPorto® 3.5 – a central fetal monitoring station with online alerts based on computerized cardiotocogram+ST event analysis

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Artificial intelligence and amniotic fluid multiomics: prediction of perinatal outcome in asymptomatic women with short cervix

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Left ventricular cardiac function in fetuses with congenital diaphragmatic hernia and the effect of fetal endoscopic tracheal occlusion

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Ultrasound assessment of fetal cardiac function

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Decision Fusion-Based Fetal Ultrasound Image Plane Classification Using Convolutional Neural Networks

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A Deep Learning Solution for Automatic Fetal Neurosonographic Diagnostic Plane Verification Using Clinical Standard Constraints

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A framework for analysis of linear ultrasound videos to detect fetal presentation and heartbeat

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Automated annotation and quantitative description of ultrasound videos of the fetal heart

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Improving preterm newborn identification in low-resource settings with machine learning

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Machine-learning-based automatic identification of fetal abdominal circumference from ultrasound images

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Standard Plane Detection in 3D Fetal Ultrasound Using an Iterative Transformation Network

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Automatic evaluation of fetal head biometry from ultrasound images using machine learning

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A Computational Model of the Fetal Circulation to Quantify Blood Redistribution in Intrauterine Growth Restriction

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Artificial intelligence assistance for fetal head biometry: Assessment of automated measurement software

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Guided Random Forests for Identification of Key Fetal Anatomy and Image Categorization in Ultrasound Scans

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Machine Learning for Fetal Growth Prediction

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Prediction of fetal state from the cardiotocogram recordings using neural network models

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

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VP-Nets : Efficient automatic localization of key brain structures in 3D fetal neurosonography

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Robotic-Assisted Ultrasound for Fetal Imaging: Evolution from Single-Arm to Dual-Arm System

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Real time processing and analysis of fetal phonocardiographic signals

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A deep learning approach to fetal-ECG signal reconstruction

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A study of an intelligent system to support decision making in the management of labour using the cardiotocograph – the INFANT study protocol

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Quality control of fetal ultrasound images: Detection of abdomen anatomical landmarks using AdaBoost

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First Trimester Noninvasive Prenatal Diagnosis: A Computational Intelligence Approach

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Fetal Cardiac Doppler Signal Processing Techniques: Challenges and Future Research Directions

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Automatic fetal body and amniotic fluid segmentation from fetal ultrasound images by encoder-decoder network with inner layers

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Automated Techniques for the Interpretation of Fetal Abnormalities: A Review

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Image Analysis Using Machine Learning: Anatomical Landmarks Detection in Fetal Ultrasound Images

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Automatic Recognition of Complete Atrioventricular Activity in Fetal Pulsed-Wave Doppler Signals

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Automatic Detection of Fetal Abnormality Using Head and Abdominal Circumference

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Features Based IUGR Diagnosis Using Variational Level Set Method and Classification Using Artificial Neural Networks

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Multi-organ Detection in 3D Fetal Ultrasound with Machine Learning

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Assessment of Haemodynamic Remodeling in Fetal Aortic Coarctation Using a Lumped Model of the Circulation

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How Do Machines Learn? Artificial Intelligence as a New Era in Medicine

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Application and Progress of Artificial Intelligence in Fetal Ultrasound

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Medical Professional Enhancement Using Explainable Artificial Intelligence in Fetal Cardiac Ultrasound Screening

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Artificial intelligence for cervical cancer screening: Scoping review, 2009–2022

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Deep Learning for Improving the Effectiveness of Routine Prenatal Screening for Major Congenital Heart Diseases

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The Role of Artificial Intelligence in Prediction, Risk Stratification, and Personalized Treatment Planning for Congenital Heart Diseases

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Accurate Detection of Septal Defects With Fetal Ultrasonography Images Using Deep Learning-Based Multiclass Instance Segmentation

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Artificial Intelligence in Pediatric Cardiology: A Scoping Review

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Artificial intelligence in obstetrics

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Challenges of Developing Robust AI for Intrapartum Fetal Heart Rate Monitoring

O’Sullivan, M., Considine, E. C., O’Riordan, M., Marnane, W. P., Rennie, J. M., & Boylan, G. B. (2021) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2021.765210 · Cited by 38 · see citing works

A Machine Learning Method for Automated Description and Workflow Analysis of First Trimester Ultrasound Scans

Yasrab, R., Fu, Z., Zhao, H., Lee, L. H., Sharma, H., Drukker, L., Papageorgiou, A. T., & Noble, J. A. (2022) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2022.3226274 · Cited by 35 · see citing works

Novel artificial intelligence approach for automatic differentiation of fetal occiput anterior and non-occiput anterior positions during labor

Ghi, T., Conversano, F., Ramirez Zegarra, R., Pisani, P., Dall'Asta, A., Lanzone, A., Lau, W., Vimercati, A., Iliescu, D. G., Mappa, I., et al. (2022) · Ultrasound in Obstetrics &amp; Gynecology · doi:10.1002/uog.23739 · Cited by 32 · see citing works

Deep Learning Technique for Congenital Heart Disease Detection Using Stacking-Based CNN-LSTM Models From Fetal Echocardiogram: A Pilot Study

Rahman, T., Al-Ruweidi, M. K. A. A., Sumon, M. S. I., Kamal, R. Y., Chowdhury, M. E. H., & Yalcin, H. C. (2023) · IEEE Access · doi:10.1109/access.2023.3316719 · Cited by 33 · see citing works

Child and Maternal Mortality Risk Factor Analysis Using Machine Learning Approaches

Sheakh, M. A., Tahosin, M. S., Hasan, M. M., et al. (2023) · International Symposium on Digital Forensics and Security (ISDFS) · doi:10.1109/isdfs58141.2023.10131826 · Cited by 30 · see citing works

Multi-centre deep learning for placenta segmentation in obstetric ultrasound with multi-observer and cross-country generalization

Andreasen, L. A., Feragen, A., Christensen, A. N., Thybo, J. K., Svendsen, M. B. S., Zepf, K., Lekadir, K., & Tolsgaard, M. G. (2023) · Scientific Reports · doi:10.1038/s41598-023-29105-x · Cited by 28 · see citing works

Advancements in Fetal Heart Rate Monitoring: A Report on Opportunities and Strategic Initiatives for Better Intrapartum Care

Lovers, A. A. K., Däumer, M., Frasch, M. G., Ugwumadu, A. H. N., Warrick, P. A., Vullings, R., Pini, N., Tolladay, J., Petersen, O. B., Lederer, C., et al. (2025) · BJOG An International Journal of Obstetrics & Gynaecology · doi:10.1111/1471-0528.18097 · Cited by 29 · see citing works

Learning deep architectures for the interpretation of first-trimester fetal echocardiography (LIFE) - a study protocol for developing an automated intelligent decision support system for early fetal echocardiography

Ungureanu, A., Marcu, A., Patru, C., Ruican, D., Nagy, R. D., Stoean, R., Stoean, C., & Iliescu, D. G. (2023) · BMC Pregnancy and Childbirth · doi:10.1186/s12884-022-05204-x · Cited by 24 · see citing works

Intelligent systems in obstetrics and midwifery: Applications of machine learning

Barbounaki, S. G., & Vivilaki, V. G. (2021) · European Journal of Midwifery · doi:10.18332/ejm/143166 · Cited by 23 · see citing works

Auto-tuning Fixed-point Precision with TVM on RISC-V Packed SIMD Extension

Yang, C.-C., Chen, Y.-R., Liao, H.-H., et al. (2022) · ACM Transactions on Design Automation of Electronic Systems · doi:10.1145/3569939 · Cited by 22 · see citing works

Prenatal diagnosis of hypoplastic left heart syndrome on ultrasound using artificial intelligence: How does performance compare to a current screening programme?

Day, T. G., Budd, S., Tan, J., Matthew, J., Skelton, E., Jowett, V., Lloyd, D. F. A., Gómez, A., Hajnal, J. V., Razavi, R., et al. (2023) · Prenatal Diagnosis · doi:10.1002/pd.6445 · Cited by 22 · see citing works

Prospective Artificial Intelligence to Dissect the Dengue Immune Response and Discover Therapeutics

Natali, E. N., Babrak, L. M., & Miho, E. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.574411 · Cited by 21 · see citing works

An ensemble-based stage-prediction machine learning approach for classifying fetal disease

Dash, D., & Kumar, M. (2024) · Healthcare Analytics · doi:10.1016/j.health.2024.100322 · Cited by 21 · see citing works

A multicenter study on two-stage transfer learning model for duct-dependent CHDs screening in fetal echocardiography

Tang, J., Liang, Y., Jiang, Y., Liu, J., Zhang, R., Huang, D., Pang, C., Huang, C. L., Luo, D., Zhou, X., et al. (2022) · npj Digital Medicine · doi:10.1038/s41746-023-00883-y · Cited by 22 · see citing works

The Diagnostic Yield of Fetal Echocardiography Indications in the Current Era

Boehme, C., Fruitman, D. S., Eckersley, L., Low, R. A., Bennett, J., McBrien, A., Alvarez, S. G. V., Pastuck, M., & Hornberger, L. K. (2021) · Journal of the American Society of Echocardiography · doi:10.1016/j.echo.2021.09.005 · Cited by 20 · see citing works

Deep Learning for the Detection of Frames of Interest in Fetal Heart Assessment from First Trimester Ultrasound

Stoean, R., Iliescu, D. G., Stoean, C., et al. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-85030-2_1 · Cited by 19 · see citing works

Inside the “black box”: Embedding clinical knowledge in data-driven machine learning for heart disease diagnosis

Meng, J., & Xing, R. (2022) · Cardiovascular Digital Health Journal · doi:10.1016/j.cvdhj.2022.10.005 · Cited by 20 · see citing works

Towards Autonomous Healthcare: Integrating Artificial Intelligence (AI) for Personalized Medicine and Disease PredictionPreprint

Rane, N. L., Choudhary, S., & Rane, J. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4637894 · Cited by 18 · see citing works

A deep learning framework for noninvasive fetal ECG signal extraction

Wahbah, M., Zitouni, M. S., Sakaji, R. A., Funamoto, K., Widatalla, N., Krishnan, A. N., Kimura, Y., & Khandoker, A. H. (2024) · Frontiers in Physiology · doi:10.3389/fphys.2024.1329313 · Cited by 16 · see citing works

Indications for fetal echocardiography: consensus and controversies among evidence‐based national and international guidelines

Robertis, V. D., Stampalija, T., Abuhamad, A., Bosco, M., Chaoui, R., Formigoni, C., Moon‐Grady, A. J., Paladini, D., Pilu, G., Ramezzana, I. G., et al. (2025) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.29224 · Cited by 18 · see citing works

The Use of Artificial Intelligence in Automation in the Fields of Gynaecology and Obstetrics – an Assessment of the State of Play

Weichert, J., Welp, A., Scharf, J. L., Dracopoulos, C., Becker, W.-H., & Gembicki, M. (2021) · Geburtshilfe und Frauenheilkunde · doi:10.1055/a-1522-3029 · Cited by 17 · see citing works

A Fetal Well-Being Diagnostic Method Based on Cardiotocographic Morphological Pattern Utilizing Autoencoder and Recursive Feature Elimination

Akmal, H., Hardalaç, F., & Ayturan, K. (2023) · Diagnostics · doi:10.3390/diagnostics13111931 · Cited by 20 · see citing works

Role of Four-Chamber Heart Ultrasound Images in Automatic Assessment of Fetal Heart: A Systematic Understanding

Gudigar, A., Raghavendra, U., Samanth, J., Vasudeva, A., Ashwal, A. J., Nayak, K., Tan, R., Ciaccio, E. J., Ooi, C. P., Barua, P. D., et al. (2022) · Informatics · doi:10.3390/informatics9020034 · Cited by 15 · see citing works

Local Preserving Class Separation Framework to Identify Gestational Diabetes Mellitus Mother Using Ultrasound Fetal Cardiac Image

Gudigar, A., Samanth, J., Raghavendra, U., Dharmik, C., Vasudeva, A., Ramachandran, P., Tan, R., Ciaccio, E. J., Molinari, F., & Acharya, U. R. (2020) · IEEE Access · doi:10.1109/access.2020.3042594 · Cited by 15 · see citing works

An improved semantic segmentation with region proposal network for cardiac defect interpretation

Nurmaini, S., Tama, B. A., Rachmatullah, M. N., Darmawahyuni, A., Sapitri, A. I., Firdaus, F., & Tutuko, B. (2022) · Neural Computing and Applications · doi:10.1007/s00521-022-07217-1 · Cited by 14 · see citing works

Abnormalities of the Width of the Four‐Chamber View and the Area, Length, and Width of the Ventricles to Identify Fetuses at High‐Risk for D‐Transposition of the Great Arteries and Tetralogy of Fallot

DeVore, G. R., Cuneo, B. F., Sklansky, M., & Satou, G. M. (2022) · Journal of Ultrasound in Medicine · doi:10.1002/jum.16060 · Cited by 13 · see citing works

Applications of artificial intelligence-powered prenatal diagnosis for congenital heart disease

Liu, X., Zhang, Y., Zhu, H., Jia, B., Wang, J., He, Y., & Zhang, H. (2024) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2024.1345761 · Cited by 14 · see citing works

A second look at intrapartum fetal surveillance and future directions

Ugwumadu, A. H. N., & Arulkumaran, S. (2022) · Journal of Perinatal Medicine · doi:10.1515/jpm-2022-0292 · Cited by 13 · see citing works

Automated Recognition of Ultrasound Cardiac Views Based on Deep Learning with Graph Constraint

Gao, Y., Zhu, Y., Liu, B., Hu, Y., Yu, G., & Guo, Y. (2021) · Diagnostics · doi:10.3390/diagnostics11071177 · Cited by 12 · see citing works

FetalMovNet: A Novel Deep Learning Model Based on Attention Mechanism for Fetal Movement Classification in US

Turkan, M., Dandıl, E., Urfalı, F. E., & Korkmaz, M. (2025) · IEEE Access · doi:10.1109/access.2025.3553548 · Cited by 14 · see citing works

A regressive encoder-decoder-based deep attention model for segmentation of fetal head in 2D-ultrasound images

Srivastava, S., Vidyarthi, A., & Jain, S. (2023) · Image and Vision Computing · doi:10.1016/j.imavis.2023.104725 · Cited by 12 · see citing works

A comprehensive scoping review on machine learning-based fetal echocardiography analysis

Hernandez-Cruz, N., Patey, O. V., Teng, C., Papageorghiou, A. T., & Noble, J. A. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2025.109666 · Cited by 12 · see citing works

Artificial intelligence in fetal echocardiography: Recent advances and future prospects

Ma, M., Sun, L., Chen, R., Zhu, J., & Zhao, B. (2024) · IJC Heart & Vasculature · doi:10.1016/j.ijcha.2024.101380 · Cited by 13 · see citing works

Segmentation atrioventricular septal defect by using convolutional neural networks based on U-NET architecture

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Prediction of low birth weight from fetal ultrasound and clinical characteristics: a comparative study between a low- and middle-income and a high-income country

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Right or wrong? Looking through the retrospectoscope to analyse predictions made a decade ago in prenatal diagnosis and fetal surgery

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Sonographer interaction with artificial intelligence: collaboration or conflict?

Day, T. G., Matthew, J., Budd, S., Hajnal, J. V., Simpson, J. M., Razavi, R., & Kainz, B. (2023) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.26238 · Cited by 10 · see citing works

Ontologies, Machine Learning and Deep Learning in Obstetrics

Malgieri, L. E. (2023) · Springer eBooks · doi:10.1007/978-3-031-10067-3_3 · Cited by 8 · see citing works

Simulator, machine learning, and artificial intelligence: Time has come to assist prenatal ultrasound diagnosis

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A Clinical Approach to Semiautomated Three-Dimensional Fetal Brain Biometry—Comparing the Strengths and Weaknesses of Two Diagnostic Tools: 5DCNS+TM and SonoCNSTM

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Artificial intelligence, machine learning and deep learning in biomedical fields: A prospect in improvising medical healthcare systems

Khan, W. H., Khan, M. S., Khan, N., Ahmad, A., Siddiqui, Z. I., Singh, R. K., & Malik, M. Z. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-21870-5.00006-6 · Cited by 8 · see citing works

A Pragmatic Approach to Fetal Monitoring via Cardiotocography Using Feature Elimination and Hyperparameter Optimization

Hardalaç, F., Akmal, H., Ayturan, K., Acharya, U. R., & Tan, R. (2022) · Interdisciplinary Sciences Computational Life Sciences · doi:10.1007/s12539-024-00647-6 · Cited by 12 · see citing works

Accurately assessing congenital heart disease using artificial intelligence

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Role of Artificial Intelligence in Congenital Heart Disease and Interventions

Holt, D. B., El‐Bokl, A., Stromberg, D., & Taylor, M. D. (2025) · Journal of the Society for Cardiovascular Angiography & Interventions · doi:10.1016/j.jscai.2025.102567 · Cited by 7 · see citing works

Development and Validation of a Novel Deep Learning Model to Predict Pharmacologic Closure of Patent Ductus Arteriosus in Premature Infants

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Artificial intelligence, radiomics and fetal ultrasound: review of literature and future perspectives

Bouachba, A., Neves, J. D. J., Royer, E., Bartin, R., Salomon, L. J., Grévent, D., & Gorincour, G. (2025) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.29172 · Cited by 8 · see citing works

Artificial Intelligence in Clinical Toxicology

Sinha, M., Praveen, G. B., Sachan, D. K., & Parthasarathi, R. (2021) · Springer eBooks · doi:10.1007/978-3-030-58080-3_137-1 · Cited by 8 · see citing works

A Differential Clinical Benefit Examination of Full Lumbar Endoscopy vs Interspinous Process Spacers in the Treatment of Spinal Stenosis: An Effect Size Meta-Analysis of Clinical Outcomes

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What Does Fetal Echocardiography Add Beyond the Anomaly Scan?

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Performance evaluation of computer-aided automated master frame selection techniques for fetal echocardiography

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A Machine Learning–Based Intrauterine Growth Restriction (IUGR) Prediction Model for Newborns

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Prediction of Late Intrauterine Growth Restriction using Machine Learning Models

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Current Status of Machine Learning and Artificial Intelligence in Cervical Cancer Screening and Diagnosis: A Systematic Review

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Keeping the Ductus Arteriosus Patent: Current Strategy and Perspectives

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Künstliche Intelligenz in der pränatalen kardialen Diagnostik

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Towards a device-independent deep learning approach for the automated segmentation of sonographic fetal brain structures: a multi-center and multi-device validation

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Machine Learning for Ischaemic Heart Disease Diagnostic Analysis

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Organ-specific learning curves of sonographers performing first-trimester anatomical screening and impact of score-based evaluation on ultrasound image quality

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Deep Learning Approach for Fetal Health Prediction

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Prediction of Fetal Abnormalities at early stage with GradientBoosting and Polynomial Feature

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Applications of Text Generation in Digital Marketing: a review

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Enhancing Predictive Models: An In-depth Analysis of Feature Selection Techniques Coupled with Boosting Algorithms

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An Integrated Approach for Pregnancy Detection Using Canny Edge Detection and Convolutional Neural Network

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Pulmonary vascular reactivity in growth restricted fetuses using computational modelling and machine learning analysis of fetal Doppler waveforms

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Ethical Considerations in Fetal Cardiology

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Implementation of resource-efficient fetal echocardiography detection algorithms in edge computing

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The application of artificial intelligence in tissue repair and regenerative medicine related to pediatric and congenital heart surgery: a narrative review

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Thoughts on the contribution of artificial intelligence ( AI ) to assessment of the fetal heart: a true scientific odyssey

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Artificial Intelligence in Clinical Toxicology

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Congenital Heart Diseases in Pregnancy

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A Study on the Association between Korotkoff Sound Signaling and Chronic Heart Failure (CHF) Based on Computer-Assisted Diagnoses

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Fetal Status Classification Based on Feature Elimination and Hyperparameter Optimization Using Cardiotocographic DataPreprint

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A Review of AI-Based Approaches for Suspected Fetal Abnormalities

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Fetal cardiac function in pregnancy affected by congenital heart disease: protocol for a multicentre prospective cohort study

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Optical Flow-Enhanced Mamba U-Net for Cardiac Phase Detection in Ultrasound Videos

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Fetal Cardiac Anomaly Detection Models Using Pattern Classification and FetalEcho_V01 Dataset

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Enhancing Fetal Cardiac Imaging With Artificial Intelligence

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AI ‐Driven Analysis of the Fetal Left Ventricular Outflow Tract

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Phenotyping Preeclampsia Using Unsupervised Machine Learning: A Prospective Cohort Study

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Employing Support Vector Machine Regression to Estimate the Fetal Gestational Age

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Anatomical structure characterization of fetal ultrasound images using texture‐based segmentation technique via an interactive MATLAB application

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ML-Based Interpretation of Cardiotocography Data: Current State and Future Research

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Prediction of fetal heart disease detection using naive bayes classifier and comparing with linear regression classifier

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Improving New Zealand Health Outcomes with Artificial Intelligence

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