[This corrects the article DOI: 10.1371/journal.pone.0183664.].
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0195858 | PLOS |
Nat Commun
January 2025
Department of Sports Medicine & Orthopedic Surgery, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou City, Zhejiang Province, China.
Clin Imaging
January 2025
Institute of Clinical sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Dept of Pediatric Radiology, The Queen Silvia Children's Hospital, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden.
Background: Congenital heart diseases (CHDs) are common birth defects. This work presents over four years of clinical experience of 4D flow cardiovascular magnetic resonance (CMR), highlighting its value for pediatric CHD.
Methods: Children with various CHD diagnoses (n = 298) were examined on a 1.
J Chem Inf Model
January 2025
Department of Life Science Informatics and Data Science, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Friedrich-Hirzebruch-Allee 5/6, Bonn D-53115, Germany.
Explaining the predictions of machine learning models is of critical importance for integrating predictive modeling in drug discovery projects. We have generated a test system for predicting isoform selectivity of phosphoinositide 3-kinase (PI3K) inhibitors and systematically analyzed correct predictions of selective inhibitors using a new methodology termed MolAnchor, which is based on the "anchors" concept from explainable artificial intelligence. The approach is designed to generate chemically intuitive explanations of compound predictions.
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