植田大樹
主な論文

Chest radiography as a biomarker of ageing: artificial intelligence-based, multi-institutional model development and validation in Japan. The Lancet Healthy Longevity. 4(9):e478-e486. 2023.
Fairness of artificial intelligence in healthcare: review and recommendations. Japanese journal of radiology. 42(1):3-15. 2023.
AI-based Virtual Synthesis of Methionine PET from Contrast-enhanced MRI: Development and External Validation Study. Radiology. 308(2):e223016. 2023.
Artificial intelligence-based model to classify cardiac functions from chest radiographs: a multi-institutional, retrospective model development and validation study. The Lancet Digital Health. 5(8):e525-e533. 2023.
ChatGPT’s Diagnostic Performance from Patient History and Imaging Findings on the Diagnosis Please Quizzes. Radiology. 308(1):e231040. 2023.
Deep learning for pneumothorax diagnosis: a systematic review and meta-analysis. European respiratory review: an official journal of the European Respiratory Society. 32(168):220259. 2023.
Evaluating GPT-4-based ChatGPT’s clinical potential on the NEJM quiz. 2(4). 2023.
Deep Learning-Based Time-to-Death Prediction Model for COVID-19 Patients Using Clinical Data and Chest Radiographs. Journal of digital imaging. 36(1):178–188. 2023.
Nervus: A Comprehensive Deep Learning Classification, Regression, and Prognostication Tool for both Medical Image and Clinical Data Analysis. arXiv [eess.IV]. DOI: 10.48550/ARXIV.2212.11113. 2022.
Artificial intelligence-based model for COVID-19 prognosis incorporating chest radiographs and clinical data; a retrospective model development and validation study. The British journal of radiology. 95(1140):20220058. 2022.
Deep learning-based algorithm for lung cancer detection on chest radiographs using the segmentation method. Scientific reports. 12(1):727. 2022.
Visual and quantitative evaluation of microcalcifications in mammograms with deep learning-based super-resolution. European journal of radiology. 154:110433. 2022.
Artificial intelligence-based detection of atrial fibrillation from chest radiographs. European radiology. 32(9):5890–5897. 2022.
Maskless 2-Dimensional Digital Subtraction Angiography Generation Model for Abdominal Vasculature using Deep Learning. Journal of vascular and interventional radiology: JVIR. 33(7):845–851. 2022.
Deep learning-based detection of parathyroid adenoma by 99mTc-MIBI scintigraphy in patients with primary hyperparathyroidism. Annals of nuclear medicine. 36(5):468–478. 2022.
Development and validation of a deep learning model for detection of breast cancers in mammography from multi-institutional datasets. PloS one. 17(3):e0265751. 2022.
Development and Validation of Artificial Intelligence–based Method for Diagnosis of Mitral Regurgitation from Chest Radiographs. Radiology: Artificial Intelligence. 4(2):e210221. 2022.
Artificial intelligence-based detection of aortic stenosis from chest radiographs. European heart journal. Digital health. 3(1):20–28. 2022.
Training, Validation, and Test of Deep Learning Models for Classification of Receptor Expressions in Breast Cancers From Mammograms. JCO precision oncology. 5:543–551. 2021.
Artificial intelligence-supported lung cancer detection by multi-institutional readers with multi-vendor chest radiographs: a retrospective clinical validation study. BMC cancer. 21(1):1120. 2021.
Deep Learning-based Angiogram Generation Model for Cerebral Angiography without Misregistration Artifacts. Radiology. 299(3):675–681. 2021.
Visualizing “featureless” regions on mammograms classified as invasive ductal carcinomas by a deep learning algorithm: the promise of AI support in radiology. Japanese journal of radiology. 39(4):333–340. 2021.
Deep Learning for MR Angiography: Automated Detection of Cerebral Aneurysms. Radiology. 290(1):187–194. 2019.
Technical and clinical overview of deep learning in radiology. Japanese journal of radiology. 37(1):15–33. 2019.