Search Results - "Pan, Ian"

Performance of Radiologists in Differentiating COVID-19 from Non-COVID-19 Viral Pneumonia at Chest CT by Bai, Harrison X, Hsieh, Ben, Xiong, Zeng, Halsey, Kasey, Choi, Ji Whae, Tran, Thi My Linh, Pan, Ian, Shi, Lin-Bo, Wang, Dong-Cui, Mei, Ji, Jiang, Xiao-Long, Zeng, Qiu-Hua, Egglin, Thomas K, Hu, Ping-Feng, Agarwal, Saurabh, Xie, Fang-Fang, Li, Sha, Healey, Terrance, Atalay, Michael K, Liao, Wei-Hua

“…Background Despite its high sensitivity in diagnosing coronavirus disease 2019 (COVID-19) in a screening population, the chest CT appearance of COVID-19…”
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Artificial Intelligence Augmentation of Radiologist Performance in Distinguishing COVID-19 from Pneumonia of Other Origin at Chest CT by Bai, Harrison X, Wang, Robin, Xiong, Zeng, Hsieh, Ben, Chang, Ken, Halsey, Kasey, Tran, Thi My Linh, Choi, Ji Whae, Wang, Dong-Cui, Shi, Lin-Bo, Mei, Ji, Jiang, Xiao-Long, Pan, Ian, Zeng, Qiu-Hua, Hu, Ping-Feng, Li, Yi-Hui, Fu, Fei-Xian, Huang, Raymond Y, Sebro, Ronnie, Yu, Qi-Zhi, Atalay, Michael K, Liao, Wei-Hua

“…Background Coronavirus disease 2019 (COVID-19) and pneumonia of other diseases share similar CT characteristics, which contributes to the challenges in…”
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The RSNA Pediatric Bone Age Machine Learning Challenge by Halabi, Safwan S, Prevedello, Luciano M, Kalpathy-Cramer, Jayashree, Mamonov, Artem B, Bilbily, Alexander, Cicero, Mark, Pan, Ian, Pereira, Lucas Araújo, Sousa, Rafael Teixeira, Abdala, Nitamar, Kitamura, Felipe Campos, Thodberg, Hans H, Chen, Leon, Shih, George, Andriole, Katherine, Kohli, Marc D, Erickson, Bradley J, Flanders, Adam E

“…Purpose The Radiological Society of North America (RSNA) Pediatric Bone Age Machine Learning Challenge was created to show an application of machine learning…”
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Deep learning-based classification of primary bone tumors on radiographs: A preliminary study by He, Yu, Pan, Ian, Bao, Bingting, Halsey, Kasey, Chang, Marcello, Liu, Hui, Peng, Shuping, Sebro, Ronnie A., Guan, Jing, Yi, Thomas, Delworth, Andrew T., Eweje, Feyisope, States, Lisa J., Zhang, Paul J., Zhang, Zishu, Wu, Jing, Peng, Xianjing, Bai, Harrison X.

“…To develop a deep learning model to classify primary bone tumors from preoperative radiographs and compare performance with radiologists. A total of 1356…”
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Deep Learning for Pulmonary Embolism Detection: Tackling the RSNA 2020 AI Challenge by Pan, Ian

“…In 2020, the Radiological Society of North America and Society of Thoracic Radiology sponsored a machine learning competition to detect and classify pulmonary…”
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PROGINS Alu sequence insertion is associated with hyperprolactinaemia but not leiomyoma susceptibility by Hsieh, Yao-Yuan, Chan, Ian-Pan, Wang, Hsin-I., Chang, Chi-Chen, Huang, Ching-Wei, Lin, Chich-Sheng

“…Summary Objective  Leiomyoma and hyperprolactinaemia are both progesterone‐dependent diseases. Hormone‐related genes, such as the progesterone receptor (PGR),…”
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Generalizable Inter-Institutional Classification of Abnormal Chest Radiographs Using Efficient Convolutional Neural Networks by Pan, Ian, Agarwal, Saurabh, Merck, Derek

“…Our objective is to evaluate the effectiveness of efficient convolutional neural networks (CNNs) for abnormality detection in chest radiographs and investigate…”
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Tackling the Radiological Society of North America Pneumonia Detection Challenge by Pan, Ian, Cadrin-Chênevert, Alexandre, Cheng, Phillip M

“…We provide overviews of deep learning approaches used by two top-placing teams for the 2018 Radiological Society of North America (RSNA) Pneumonia Detection…”
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NIMG-66. DEFINING PROGRESSIVE DISEASE: LOCALIZING VOXEL-AT-RISK ON MAGNETIC RESONANCE IMAGING USING DEEP LEARNING by Freeman, Nicolas, Pan, Ian, Youssef, Gilbert, Wen, Patrick, Huang, Raymond

“…Abstract Follow-up magnetic resonance imaging (MRI) of post-treatment glioblastoma (GBM) can be diagnostically challenging in differentiating progressive…”
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Artificial intelligence in neuroimaging of brain tumors: reality or still promise? by Pan, Ian, Huang, Raymond Y

“…To provide an updated overview of artificial intelligence (AI) applications in neuro-oncologic imaging and discuss current barriers to wider clinical adoption…”
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Artificial Intelligence Class Activation Mapping of Bone Age by Kitamura, Felipe C, Pan, Ian

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Deep Learning: An Update for Radiologists by Cheng, Phillip M., Montagnon, Emmanuel, Yamashita, Rikiya, Pan, Ian, Cadrin-Chênevert, Alexandre, Perdigón Romero, Francisco, Chartrand, Gabriel, Kadoury, Samuel, Tang, An

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A SYSTEMATIC REVIEW OF DEEP LEARNING APPLICATIONS FOR OPTICAL COHERENCE TOMOGRAPHY IN AGE-RELATED MACULAR DEGENERATION by Paul, Samantha K., Pan, Ian, Sobol, Warren M.

“…Purpose: To survey the current literature regarding applications of deep learning to optical coherence tomography in age-related macular degeneration (AMD)…”
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Deep Learning in Neuroradiology: A Systematic Review of Current Algorithms and Approaches for the New Wave of Imaging Technology by Yao, Anthony D, Cheng, Derrick L, Pan, Ian, Kitamura, Felipe

“…To systematically review and synthesize the current literature and to develop a compendium of technical characteristics of existing deep learning applications…”
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Evaluation of a convolutional neural network for ovarian tumor differentiation based on magnetic resonance imaging by Wang, Robin, Cai, Yeyu, Lee, Iris K., Hu, Rong, Purkayastha, Subhanik, Pan, Ian, Yi, Thomas, Tran, Thi My Linh, Lu, Shaolei, Liu, Tao, Chang, Ken, Huang, Raymond Y., Zhang, Paul J., Zhang, Zishu, Xiao, Enhua, Wu, Jing, Bai, Harrison X.

“…Objectives There currently lacks a noninvasive and accurate method to distinguish benign and malignant ovarian lesion prior to treatment. This study developed…”
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Machine Learning for Social Services: A Study of Prenatal Case Management in Illinois by Pan, Ian, Nolan, Laura B, Brown, Rashida R, Khan, Romana, van der Boor, Paul, Harris, Daniel G, Ghani, Rayid

“…To evaluate the positive predictive value of machine learning algorithms for early assessment of adverse birth risk among pregnant women as a means of…”
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SCU‐Net: A deep learning method for segmentation and quantification of breast arterial calcifications on mammograms by Guo, Xiaoyuan, O'Neill, W. Charles, Vey, Brianna, Yang, Tianen Christopher, Kim, Thomas J., Ghassemi, Maryzeh, Pan, Ian, Gichoya, Judy Wawira, Trivedi, Hari, Banerjee, Imon

“…Purpose Measurements of breast arterial calcifications (BAC) can offer a personalized, non‐invasive approach to risk‐stratify women for cardiovascular diseases…”
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Clinical Artificial Intelligence Applications in Radiology: Neuro by Kitamura, Felipe Campos, Pan, Ian, Ferraciolli, Suely Fazio, Yeom, Kristen W, Abdala, Nitamar

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Clinical Artificial Intelligence Applications in Radiology by Kitamura, Felipe Campos, Pan, Ian, Ferraciolli, Suely Fazio, Yeom, Kristen W., Abdala, Nitamar

“…Radiologists have been at the forefront of the digitization process in medicine. Artificial intelligence (AI) is a promising area of innovation, particularly…”
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Federated Deep Learning to More Reliably Detect Body Part for Hanging Protocols, Relevant Priors, and Workflow Optimization by Filice, Ross W., Stein, Anouk, Pan, Ian, Shih, George

“…Preparing radiology examinations for interpretation requires prefetching relevant prior examinations and implementing hanging protocols to optimally display…”
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