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Head CT deep learning model is highly accurate for early infarct estimation

Scientific reports, 2023-01, Vol.13 (1), p.189-189, Article 189

2023

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Development and clinical application of a deep learning model to identify acute infarct on magnetic resonance imaging

Scientific reports, 2022-02, Vol.12 (1), p.2154-2154, Article 2154

2022

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From Machine Learning to Patient Outcomes: A Comprehensive Review of AI in Pancreatic Cancer

Diagnostics (Basel), 2024-01, Vol.14 (2), p.174

2024

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Enrichment of lung cancer computed tomography collections with AI-derived annotations

Scientific data, 2024-01, Vol.11 (1), p.25-25, Article 25

2024

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Improving the repeatability of deep learning models with Monte Carlo dropout

NPJ digital medicine, 2022-11, Vol.5 (1), p.174-11, Article 174

2022

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Population-Scale CT-based Body Composition Analysis of a Large Outpatient Population Using Deep Learning to Derive Age-, Sex-, and Race-specific Reference Curves

Radiology, 2021-02, Vol.298 (2), p.319-329

2021

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

Medical image analysis, 2017-02, Vol.36, p.147-161

2017

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The influence of anisotropy on the clinical target volume of brain tumor patients

Physics in medicine & biology, 2024-02, Vol.69 (3), p.35006

2024

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ECGAug: A novel method of generating augmented annotated electrocardiogram QRST complexes and rhythm strips

Computers in biology and medicine, 2021-07, Vol.134, p.104408-104408, Article 104408

2021

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Utility of Normalized Body Composition Areas, Derived From Outpatient Abdominal CT Using a Fully Automated Deep Learning Method, for Predicting Subsequent Cardiovascular Events

American journal of roentgenology (1976), 2023-02, Vol.220 (2), p.236

2023

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Machine Learning for Adrenal Gland Segmentation and Classification of Normal and Adrenal Masses at CT

Radiology, 2023-02, Vol.306 (2), p.e220101-e220101

2023

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Multilevel Body Composition Analysis on Chest Computed Tomography Predicts Hospital Length of Stay and Complications After Lobectomy for Lung Cancer: A Multicenter Study

Annals of surgery, 2022-05, Vol.275 (5), p.e708

2022

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The Trials and Tribulations of Assembling Large Medical Imaging Datasets for Machine Learning Applications

Journal of digital imaging, 2021-12, Vol.34 (6), p.1424-1429

2021

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Not without Context—A Multiple Methods Study on Evaluation and Correction of Automated Brain Tumor Segmentations by Experts

Academic radiology, 2024-04, Vol.31 (4), p.1572-1582

2024

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Machine learning-based detection of sarcopenic obesity and association with adverse outcomes in patients undergoing surgical treatment for spinal metastases

Journal of neurosurgery. Spine, 2024-03, Vol.40 (3), p.291

2024

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Temporal HeartNet: Towards Human-Level Automatic Analysis of Fetal Cardiac Screening Video

Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017, p.341-349

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Muscle Loss Is Associated with Overall Survival in Patients with Metastatic Colorectal Cancer Independent of Tumor Mutational Status and Weight Loss

The oncologist (Dayton, Ohio), 2021-06, Vol.26 (6), p.e963-e970

2021

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Highdicom: a Python Library for Standardized Encoding of Image Annotations and Machine Learning Model Outputs in Pathology and Radiology

Journal of digital imaging, 2022-12, Vol.35 (6), p.1719-1737

2022

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Abnormal vascular structure and function within brain metastases is linked to pembrolizumab resistance

Neuro-oncology (Charlottesville, Va.), 2024-05, Vol.26 (5), p.965-974

2024

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A Fully Automated Deep Learning Pipeline for Multi-Vertebral Level Quantification and Characterization of Muscle and Adipose Tissue on Chest CT Scans

Radiology. Artificial intelligence, 2022-01, Vol.4 (1), p.e210080-e210080

2022

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M-SiSSR: Regional Endocardial Function Using Multilabel Simultaneous Subdivision Surface Registration

Functional Imaging and Modeling of the Heart, 2021-06, p.242-252

2021

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Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor Segmentation

Radiology. Artificial intelligence, 2024-01, Vol.6 (1), p.e220231-e220231

2024

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Object localisation in fetal ultrasound images using invariant features

2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 2015, p.156-159

2015

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IEEE_Xplore

568 ASSOCIATION OF VISCERAL ADIPOSITY WITH INCIDENT AND RECURRENT DIVERTICULITIS IN AN ELECTRONIC HEALTH RECORDBASED COHORT STUDY

Gastroenterology (New York, N.Y. 1943), 2024-05, Vol.166 (5), p.S-135-S-135

2024

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Automated characterization of the fetal heart in ultrasound images using fully convolutional neural networks

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), 2017, p.671-674

2017

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IEEE_Xplore

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Head CT deep learning model is highly accurate for early infarct estimation

Development and clinical application of a deep learning model to identify acute infarct on magnetic resonance imaging

From Machine Learning to Patient Outcomes: A Comprehensive Review of AI in Pancreatic Cancer

Enrichment of lung cancer computed tomography collections with AI-derived annotations

Improving the repeatability of deep learning models with Monte Carlo dropout

Population-Scale CT-based Body Composition Analysis of a Large Outpatient Population Using Deep Learning to Derive Age-, Sex-, and Race-specific Reference Curves

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

The influence of anisotropy on the clinical target volume of brain tumor patients

ECGAug: A novel method of generating augmented annotated electrocardiogram QRST complexes and rhythm strips

Utility of Normalized Body Composition Areas, Derived From Outpatient Abdominal CT Using a Fully Automated Deep Learning Method, for Predicting Subsequent Cardiovascular Events

Machine Learning for Adrenal Gland Segmentation and Classification of Normal and Adrenal Masses at CT

Multilevel Body Composition Analysis on Chest Computed Tomography Predicts Hospital Length of Stay and Complications After Lobectomy for Lung Cancer: A Multicenter Study

The Trials and Tribulations of Assembling Large Medical Imaging Datasets for Machine Learning Applications

Not without Context—A Multiple Methods Study on Evaluation and Correction of Automated Brain Tumor Segmentations by Experts

Machine learning-based detection of sarcopenic obesity and association with adverse outcomes in patients undergoing surgical treatment for spinal metastases

Temporal HeartNet: Towards Human-Level Automatic Analysis of Fetal Cardiac Screening Video

Muscle Loss Is Associated with Overall Survival in Patients with Metastatic Colorectal Cancer Independent of Tumor Mutational Status and Weight Loss

Highdicom: a Python Library for Standardized Encoding of Image Annotations and Machine Learning Model Outputs in Pathology and Radiology

Abnormal vascular structure and function within brain metastases is linked to pembrolizumab resistance

A Fully Automated Deep Learning Pipeline for Multi-Vertebral Level Quantification and Characterization of Muscle and Adipose Tissue on Chest CT Scans

M-SiSSR: Regional Endocardial Function Using Multilabel Simultaneous Subdivision Surface Registration

Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor Segmentation

Object localisation in fetal ultrasound images using invariant features

568 ASSOCIATION OF VISCERAL ADIPOSITY WITH INCIDENT AND RECURRENT DIVERTICULITIS IN AN ELECTRONIC HEALTH RECORDBASED COHORT STUDY

Automated characterization of the fetal heart in ultrasound images using fully convolutional neural networks

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