Assessment of Pulmonary Vascular Disease and Therapy with Machine Learning and Artificial Intelligence Archives

Artificial intelligence in neonatal hemodynamics: toward earlier and more reliable detection of pulmonary hypertension

Gabriel Altit, Guilherme Sant’AnnaMontreal Children’s Hospital and McGill University.Canada Pediatric ResearchPediatr Res 2026; DOI: 10.1038/s41390-026-05461-y AbstractAbstract Not Available CategoryClass I. Persistent Pulmonary Hypertension of the NewbornClass III. Pulmonary Hypertension Associated with Lung DiseaseAssessment of Pulmonary Vascular Disease and Therapy with Machine Learning and Artificial Intelligence Age Focus: Pediatric Pulmonary Vascular Disease Fresh or Filed Publication: Fresh

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The Pediatric Pulmonary Hypertension International Risk Score: A Prediction Model for Outcomes Using Machine Learning

Megan Griffiths, Bhargava K. Chinni, Chantel Lokhorst, Johannes M. Douwes, Lynn A. Sleeper, Jennifer Tingo, Steven H. Abman, Erika B. Rosenzweig, Jennifer E. Schramm, Eric D. Austin, Mary P. Mullen, Alba Torrent-Vernetta, Carlos Labrandero, Raymond Benza, Maria Jesus del Cerro, Rolf M. F. Berger, Cedric Manlhiot, Allen D. EverettUT Southwestern Medical Center. Johns Hopkins University.

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Development and validation of a nomogram prediction model for mild pulmonary arterial hypertension risk in children with left-to-right shunt congenital heart disease

Suyuan Qin, Lifeng Shang, Danyan Su, Bingbing Ye, Yuqin Huang, Yanyun Huang, Yusheng PangFirst Affiliated Hospital of Guangxi Medical University, Difficult and Critical Illness Center and the Pediatric Clinical Medical Research Center of Guangxi.China MedicineMedicine 2026; 105:DOI: 10.1097/MD.0000000000050136 AbstractMild pulmonary arterial hypertension (PAH) represents an early and potentially reversible complication stage in children with congenital structural

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The Role of Machine Learning and Artificial Intelligence in Drug Discovery and Clinical Care of Pulmonary Hypertension

Evelyne Bischof, Chaim Haber, Niklas LidströmerShanghai University of Medicine and Health Sciences. Sheba Medical Center, Grey School of Medicine and Tel Aviv University. University of Copenhagen. Karolinska Institutet. China, Israel, Denmark and Sweden Heart Failure ClinicsHeart Fail Clin 2026; 22: 361-370DOI: 10.1016/j.hfc.2026.02.009 AbstractPulmonary hypertension (PH) is a severe and oftentimes fatal disease with a high degree

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Adapting the REVEAL Lite 2 score to the pediatric population through machine learning: insights from the REHIPED registry for pediatric pulmonary hypertension

Julia Playán-Escribano, Carlos Labrandero de Lera, Leticia Albert de la Torre, Alejandro Rodríguez-Ogando, Antonio Moreno-Galdó, Inmaculada Guillén Rodríguez, Anna Sabaté-Rotés, Amparo Moya-Bonora, Lina María Caicedo Cuenca, María Jesús del Cerro, on behalf of the REHIPED investigatorsHospital General Universitario Gregorio Marañón. Hospital Universitario del Sureste, Arganda del Rey. Universidad Complutense de Madrid. Hospital Universitario La Paz. Hospital Universitario 12 de Octubre. Hospital General Universitario Gregorio Marañón. Hospital Universitari Vall d’Hebron, Vall d’Hebron Barcelona Hospital Campus,

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Predicting pulmonary hypertension in infants with bronchopulmonary dysplasia

Henry P. Foote, Minghui Sun, Benjamin Alan Goldstein, Kevin D. Hill, Rachel G. Greenberg, Samuel J. Gentle, Kanecia O. Zimmerman, Rishikesan Kameleswaran, Veeral N. Tolia, Matthew M. Laughon, Wesley Jackson, Christoph P. HornikDuke University Medical Center and Duke University. Yale University School of Medicine. Baylor University Medical Center. University of North Carolina. United States Journal

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Deep Learning-Based Prediction of Cardiopulmonary Disease in Retinal Images of Premature Infants

Praveer Singh, Sourav Kumar, Riya Tyagi, Benjamin K. Young, Brian K. Jordan, Brian Scottoline, Patrick D. Evers, Susan Ostmo, Aaron S. Coyner, Wei-Chun Lin, Aarushi Gupta, Deniz Erdogmus, Paul Chan, Emily A. McCourt, James S. Barry, Cindy T. McEvoy, Micheal F. Chiang, Peter Campbell, Jayashree Kalpathy-CramerUniversity of Colorado School of Medicine. Massachusetts General Hospital and

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