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CAD and AI for breast cancer-recent development and challenges

British journal of radiology, 2020-04, Vol.93 (1108), p.20190580-20190580

2020

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Urinary bladder segmentation in CT urography using deep-learning convolutional neural network and level sets

Medical physics (Lancaster), 2016-04, Vol.43 (4), p.1882-1896

2016

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Bladder Cancer Treatment Response Assessment in CT using Radiomics with Deep-Learning

Scientific reports, 2017-08, Vol.7 (1), p.8738-12, Article 8738

2017

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Deep Learning in Medical Image Analysis

Advances in experimental medicine and biology, 2020, Vol.1213, p.3-21

2020

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Multiscale bilateral filtering for improving image quality in digital breast tomosynthesis

Medical physics (Lancaster), 2015-01, Vol.42 (1), p.182-195

2015

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Computer‐aided diagnosis in the era of deep learning

Medical physics (Lancaster), 2020-06, Vol.47 (5), p.e218-e227

2020

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Data drift in medical machine learning: implications and potential remedies

British journal of radiology, 2023-10, Vol.96 (1150), p.20220878-20220878

2023

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Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography

Medical physics (Lancaster), 2016-12, Vol.43 (12), p.6654-6666

2016

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Diagnostic Accuracy of CT for Prediction of Bladder Cancer Treatment Response with and without Computerized Decision Support

Academic radiology, 2019-09, Vol.26 (9), p.1137-1145

2019

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Detection of Severe Lung Infection on Chest Radiographs of COVID-19 Patients: Robustness of AI Models across Multi-Institutional Data

Diagnostics (Basel), 2024-02, Vol.14 (3), p.341

2024

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Risks of feature leakage and sample size dependencies in deep feature extraction for breast mass classification

Medical physics (Lancaster), 2021-06, Vol.48 (6), p.2827-2837

2021

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Methodology for Good Machine Learning with Multi‐Omics Data

Clinical pharmacology and therapeutics, 2024-04, Vol.115 (4), p.745-757

2024

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Deep‐learning convolutional neural network: Inner and outer bladder wall segmentation in CT urography

Medical physics (Lancaster), 2019-02, Vol.46 (2), p.634-648

2019

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Effect of Dose Level on Radiologists’ Detection of Microcalcifications in Digital Breast Tomosynthesis: An Observer Study with Breast Phantoms

Academic radiology, 2022-01, Vol.29, p.S42-S49

2022

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Deep Learning Approach for Assessment of Bladder Cancer Treatment Response

Tomography (Ann Arbor), 2019-03, Vol.5 (1), p.201-208

2019

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Computer-aided detection of clustered microcalcifications in multiscale bilateral filtering regularized reconstructed digital breast tomosynthesis volume

Medical physics (Lancaster), 2014-02, Vol.41 (2), p.021901-n/a

2014

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Bladder Cancer Segmentation in CT for Treatment Response Assessment: Application of Deep-Learning Convolution Neural Network-A Pilot Study

Tomography (Ann Arbor), 2016-12, Vol.2 (4), p.421-429

2016

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Intraobserver Variability in Bladder Cancer Treatment Response Assessment With and Without Computerized Decision Support

Tomography (Ann Arbor), 2020-06, Vol.6 (2), p.194-202

2020

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Restorable Synthesis: Average Synthetic Segmentation Converges to a Polygon Approximation of an Object Contour in Medical Images

2024 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI), 2024, p.77-80

2024

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IEEE_Xplore

Artificial intelligence in medicine: mitigating risks and maximizing benefits via quality assurance, quality control, and acceptance testing

BJR artificial intelligence, 2024-01, Vol.1 (1), p.ubae003-ubae003

2024

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AI and machine learning in medical imaging: key points from development to translation

BJR artificial intelligence, 2024-01, Vol.1 (1), p.ubae006-ubae006

2024

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Computer-Aided Diagnosis of Breast Cancer with Tomosynthesis Imaging

Medical Image Analysis and Informatics, 2018, p.241-268

1, 2018

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Diversity Oriented Synthesis of Indoloazepinobenzimidazole and Benzimidazotriazolobenzodiazepine from N 1 ‐Alkyne‐1,2‐diamines

Chemistry : a European journal, 2015-12, Vol.21 (51), p.18828-18833

2015

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One-Pot Synthesis of Highly Fluorescent Pyrido[1,2-a]indole Derivatives through CH/NH Activation: Photophysical Investigations and Application in Cell Imaging

Chemistry : a European journal, 2014-10, Vol.20 (44), p.14344-14350

2014

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CAD and AI for breast cancer-recent development and challenges

Urinary bladder segmentation in CT urography using deep-learning convolutional neural network and level sets

Bladder Cancer Treatment Response Assessment in CT using Radiomics with Deep-Learning

Deep Learning in Medical Image Analysis

Multiscale bilateral filtering for improving image quality in digital breast tomosynthesis

Computer‐aided diagnosis in the era of deep learning

Data drift in medical machine learning: implications and potential remedies

Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography

Diagnostic Accuracy of CT for Prediction of Bladder Cancer Treatment Response with and without Computerized Decision Support

Detection of Severe Lung Infection on Chest Radiographs of COVID-19 Patients: Robustness of AI Models across Multi-Institutional Data

Risks of feature leakage and sample size dependencies in deep feature extraction for breast mass classification

Computerized Decision Support for Bladder Cancer Treatment Response Assessment in CT Urography: Effect on Diagnostic Accuracy in Multi-Institution Multi-Specialty Study

Methodology for Good Machine Learning with Multi‐Omics Data

Deep‐learning convolutional neural network: Inner and outer bladder wall segmentation in CT urography

Effect of Dose Level on Radiologists’ Detection of Microcalcifications in Digital Breast Tomosynthesis: An Observer Study with Breast Phantoms

Deep Learning Approach for Assessment of Bladder Cancer Treatment Response

Computer-aided detection of clustered microcalcifications in multiscale bilateral filtering regularized reconstructed digital breast tomosynthesis volume

Bladder Cancer Segmentation in CT for Treatment Response Assessment: Application of Deep-Learning Convolution Neural Network-A Pilot Study

Intraobserver Variability in Bladder Cancer Treatment Response Assessment With and Without Computerized Decision Support

Restorable Synthesis: Average Synthetic Segmentation Converges to a Polygon Approximation of an Object Contour in Medical Images

Artificial intelligence in medicine: mitigating risks and maximizing benefits via quality assurance, quality control, and acceptance testing

AI and machine learning in medical imaging: key points from development to translation

Computer-Aided Diagnosis of Breast Cancer with Tomosynthesis Imaging

Diversity Oriented Synthesis of Indoloazepinobenzimidazole and Benzimidazotriazolobenzodiazepine from N 1 ‐Alkyne‐1,2‐diamines

One-Pot Synthesis of Highly Fluorescent Pyrido[1,2-a]indole Derivatives through CH/NH Activation: Photophysical Investigations and Application in Cell Imaging

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