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Author Details

Felipe C Kitamura
Universidade Federal de Sao Paulo
2016
28
13
PMIDPaper TitleJournal TitlePublished Year
36604467Head CT deep learning model is highly accurate for early infarct estimation.Sci Rep2023
37795143The RSNA Cervical Spine Fracture CT Dataset.Radiol Artif Intell2023
37407841Reproducibility of Deep Learning Algorithms Developed for Medical Imaging Analysis: A Systematic Review.J Digit Imaging2023
34842954Editorial Comment: Cost-effectiveness of brain MRI in stroke emergency patients.Eur Radiol2022
35866818Multi-population generalizability of a deep learning-based chest radiograph severity score for COVID-19.Medicine (Baltimore)2022
33442676Federated Learning used for predicting outcomes in SARS-COV-2 patients.Res Sq2021
33854271The quest for reproducibility.Radiol Bras2021
33514852Deep COVID DeteCT: an international experience on COVID-19 lung detection and prognosis using chest CT.NPJ Digit Med2021
33676912Trustworthiness of Artificial Intelligence Models in Radiology and the Role of Explainability.J Am Coll Radiol2021
33524039Machine learning model for predicting severity prognosis in patients infected with COVID-19: Study protocol from COVID-AI Brasil.PLoS One2021
34526699Federated learning for predicting clinical outcomes in patients with COVID-19.Nat Med2021
34689869Clinical Artificial Intelligence Applications in Radiology: Neuro.Radiol Clin North Am2021
34350414Natural Language Processing of Radiology Text Reports: Interactive Text Classification.Radiol Artif Intell2021
34350408A Deep Learning-based Model for Detecting Abnormalities on Brain MR Images for Triaging: Preliminary Results from a Multisite Experience.Radiol Artif Intell2021
34075194Automated coronary calcium scoring using deep learning with multicenter external validation.NPJ Digit Med2021
33937862The RSNA Pulmonary Embolism CT Dataset.Radiol Artif Intell2021
33937854Magician's Corner: 8: How to Connect an Artificial Intelligence Tool to PACS.Radiol Artif Intell2021
34136815Magician's Corner: 9. Performance Metrics for Machine Learning Models.Radiol Artif Intell2021
33399506The RSNA International COVID-19 Open Radiology Database (RICORD).Radiology2021
32995811Improvement and Multi-Population Generalizability of a Deep Learning-Based Chest Radiograph Severity Score for COVID-19.medRxiv2020
33778590Regarding "Serial Quantitative Chest CT Assessment of COVID-19: Deep-Learning Approach".Radiol Cardiothorac Imaging2020
33939782Erratum: Construction of a Machine Learning Dataset through Collaboration: The RSNA 2019 Brain CT Hemorrhage Challenge.Radiol Artif Intell2020
33937836Reproducible Artificial Intelligence Research Requires Open Communication of Complete Source Code.Radiol Artif Intell2020
33937827Construction of a Machine Learning Dataset through Collaboration: The RSNA 2019 Brain CT Hemorrhage Challenge.Radiol Artif Intell2020
33937816Deep Learning in Neuroradiology: A Systematic Review of Current Algorithms and Approaches for the New Wave of Imaging Technology.Radiol Artif Intell2020
31950302Using DICOM Metadata for Radiological Image Series Categorization: a Feasibility Study on Large Clinical Brain MRI Datasets.J Digit Imaging2020
30480490The RSNA Pediatric Bone Age Machine Learning Challenge.Radiology2019
27034831Diffusion-Weighted Imaging with Color-Coded Images: Towards a Reduction in Reading Time While Keeping a Similar Accuracy.Radiol Res Pract2016
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Collaborators

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Inc., University of California san francisco
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Sirio Libanes Hospital
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Chief Science Officer ACR Data Science Institute, Massachusetts General Hospital
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Radiology Institute, University of Sao Paulo Hospital of Clinics
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Mount Sinai Health System and University Health Network
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Massachusetts General Hospital
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Mount Sinai Hospital
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Self-Defense Forces Central Hospital
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Center for Advanced Magnetic Resonance Development (M.R.B.), Duke University
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Hasso Plattner Institute for Digital Health, Icahn School of Medicine at Mount Sinai
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Technical University of Munich (TUM)
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National Cancer Institute, National Institutes of Health
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Massachusetts General Hospital, Harvard University
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Yeungnam University Hospital
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Medical Review and Pharmaceutical Benefits Division
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