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Synthesizing information from multiple data sources plays a crucial role in the practice of modern medicine.
The influence of clinical information on the reporting of ct by radiologists
Adones Leslie, AJ Jones, and PR Goddard · 2000
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Pulmonary embolism mortality in the united states, 1979-1998: an analysis using multiple-cause mortality data
Kenneth T Horlander, David M Mannino, and Kenneth V Leeper · 2003
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Severity of acute pulmonary embolism: evaluation of a new spiral ct angiographic score in correlation with echocardiographic data
Ioana Mastora, Martine Remy-Jardin, Pascal Masson, Eric Galland, Valérie Delannoy, Jean-Jacques Bauchart, and Jacques Remy · 2003
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Diagnosing pulmonary embolism: running after the decreasing prevalence of cases among suspected patients
Grégoire Le Gal and Henri Bounameaux · 2004
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Accuracy of information on imaging requisitions: does it matter?
Mervyn D Cohen · 2007
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Delay and misdiagnosis in sub-massive and non-massive acute pulmonary embolism
José Luis Alonso-Martínez, FJ Anniccherico Sánchez, and MA Urbieta Echezarreta · 2010
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Ct scan findings of emphysema predict mortality in copd
Akane Haruna, Shigeo Muro, Yasutaka Nakano, Tadashi Ohara, Yuma Hoshino, Emiko Ogawa, Toyohiro Hirai, Akio Niimi, Koichi Nishimura, Kazuo Chin, et al · 2010
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An official american thoracic society/society of thoracic radiology clinical practice guideline: evaluation of suspected pulmonary embolism in pregnancy
Ann N Leung, Todd M Bull, Roman Jaeschke, Charles J Lockwood, Phillip M Boiselle, Lynne M Hurwitz, Andra H James, Laurence B McCullough, Yusuf Menda, Michael J Paidas, et al · 2011
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American thoracic society documents: an official american thoracic society/society of thoracic radiology clinical practice guideline—evaluation of suspected pulmonary embolism in pregnancy
Ann N Leung, Todd M Bull, Roman Jaeschke, Charles J Lockwood, Phillip M Boiselle, Lynne M Hurwitz, Andra H James, Laurence B McCullough, Yusuf Menda, Michael J Paidas, et al · 2012
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Changes in pesi scores predict mortality in intermediate-risk patients with acute pulmonary embolism
Lisa Moores, Celia Zamarro, Vicente Gómez, Drahomir Aujesky, Leticia García, Rosa Nieto, Roger Yusen, and David Jiménez · 2013
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About uk biobank, 2014
UK Biobank · 2014
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Provider-to-provider communication in dermatology and implications of missing clinical information in skin biopsy requisition forms: a systematic review
Nneka I Comfere, Olayemi Sokumbi, Victor M Montori, Annie LeBlanc, Larry J Prokop, M Hassan Murad, and Jon C Tilburt · 2014
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A novel approach for multimodal medical image fusion
Zhaodong Liu, Hongpeng Yin, Yi Chai, and Simon X Yang · 2014
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A new contrast based multimodal medical image fusion framework
Gaurav Bhatnagar, QM Jonathan Wu, and Zheng Liu · 2015
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Dermatopathologists’ concerns and challenges with clinical information in the skin biopsy requisition form: a mixed-methods study
Nneka I Comfere, Margot S Peters, Sarah Jenkins, Kandace Lackore, Kathleen Yost, and Jon Tilburt · 2015
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Predictive value of computed tomography in acute pulmonary embolism: systematic review and meta-analysis
Felix G Meinel, John W Nance Jr, U Joseph Schoepf, Verena S Hoffmann, Kolja M Thierfelder, Philip Costello, Samuel Z Goldhaber, and Fabian Bamberg · 2015
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30-day mortality in acute pulmonary embolism: prognostic value of clinical scores and anamnestic features
Andreas Gunter Bach, Bettina-Maria Taute, Nansalmaa Baasai, Andreas Wienke, Hans Jonas Meyer, Dominik Schramm, and Alexey Surov · 2016
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Preparing a collection of radiology examinations for distribution and retrieval
Dina Demner-Fushman, Marc D Kohli, Marc B Rosenman, Sonya E Shooshan, Laritza Rodriguez, Sameer Antani, George R Thoma, and Clement J McDonald · 2016
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Mimic-iii, a freely accessible critical care database
Alistair EW Johnson, Tom J Pollard, Lu Shen, Li-wei H Lehman, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, and Roger G Mark · 2016
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A review of imaging modalities in pulmonary hypertension
M. Ascha, R. D. Renapurkar, and A. R. Tonelli · 2017
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Clinical characteristics associated with diagnostic delay of pulmonary embolism in primary care: a retrospective observational study
Janneke MT Hendriksen, Marleen Koster-van Ree, Marcus J Morgenstern, Ruud Oudega, Roger EG Schutgens, Karel GM Moons, and Geert-Jan Geersing · 2017
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Lightgbm: A highly efficient gradient boosting decision tree
Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, and Tie-Yan Liu · 2017
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Multi-stage diagnosis of alzheimer’s disease with incomplete multimodal data via multi-task deep learning
Kim-Han Thung, Pew-Thian Yap, and Dinggang Shen · 2017
Cited alongside, same era.
The uk biobank resource with deep phenotyping and genomic data
Clare Bycroft, Colin Freeman, Desislava Petkova, Gavin Band, Lloyd T Elliott, Kevin Sharp, Allan Motyer, Damjan Vukcevic, Olivier Delaneau, Jared O’Connell, et al · 2018
Cited alongside, same era.
Glaucoma–authors’ reply
Jost B Jonas, Tin Aung, Rupert R Bourne, Alain M Bron, Robert Ritch, and Songhomitra Panda-Jonas · 2018
Cited alongside, same era.
A feature fusion system for basal cell carcinoma detection through data-driven feature learning and patient profile
P Kharazmi, S Kalia, H Lui, ZJ Wang, and TK Lee · 2018
Cited alongside, same era.
Bone age assessment model based on multi-dimensional feature fusion using deep learning
Ming-Qian LIU · 2018
Cited alongside, same era.
Behrt: transformer for electronic health records
Yikuan Li, Shishir Rao, José Roberto Ayala Solares, Abdelaali Hassaine, Rema Ramakrishnan, Dexter Canoy, Yajie Zhu, Kazem Rahimi, and Gholamreza Salimi-Khorshidi · 2020
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The uk biobank imaging enhancement of 100,000 participants: rationale, data collection, management and future directions
Thomas J Littlejohns, Jo Holliday, Lorna M Gibson, Steve Garratt, Niels Oesingmann, Fidel Alfaro-Almagro, Jimmy D Bell, Chris Boultwood, Rory Collins, Megan C Conroy, et al · 2020
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Evaluation of acute pulmonary embolism and clot burden on ctpa with deep learning
Weifang Liu, Min Liu, Xiaojuan Guo, Peiyao Zhang, Ling Zhang, Rongguo Zhang, Han Kang, Zhenguo Zhai, Xincao Tao, Jun Wan, et al · 2020
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Detection of microcytic hypochromia using cbc and blood film features extracted from convolution neural network by different classifiers
Shikha Purwar, Rajiv Kumar Tripathi, Ravi Ranjan, and Renu Saxena · 2020
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The rsna pulmonary embolism ct dataset
Errol Colak, Felipe C Kitamura, Stephen B Hobbs, Carol C Wu, Matthew P Lungren, Luciano M Prevedello, Jayashree Kalpathy-Cramer, Robyn L Ball, George Shih, Anouk Stein, et al · 2021
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Predicting cancer outcomes from histology and genomics using convolutional networks
Pooya Mobadersany, Safoora Yousefi, Mohamed Amgad, David A Gutman, Jill S Barnholtz-Sloan, José E Velázquez Vega, Daniel J Brat, and Lee AD Cooper · 2018
Cited alongside, same era.
Scalable and accurate deep learning with electronic health records
Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M Dai, Nissan Hajaj, Michaela Hardt, Peter J Liu, Xiaobing Liu, Jake Marcus, Mimi Sun, et al · 2018
Cited alongside, same era.
Tienet: Text-image embedding network for common thorax disease classification and reporting in chest x-rays
Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, and Ronald M Summers · 2018
Cited alongside, same era.
Multimodal skin lesion classification using deep learning
Jordan Yap, William Yolland, and Philipp Tschandl · 2018
Cited alongside, same era.
Comparative effectiveness of convolutional neural network (cnn) and recurrent neural network (rnn) architectures for radiology text report classification
Imon Banerjee, Yuan Ling, Matthew C Chen, Sadid A Hasan, Curtis P Langlotz, Nathaniel Moradzadeh, Brian Chapman, Timothy Amrhein, David Mong, Daniel L Rubin, et al · 2019
Cited alongside, same era.
A machine-learning approach using pet-based radiomics to predict the histological subtypes of lung cancer
Seung Hyup Hyun, Mi Sun Ahn, Young Wha Koh, and Su Jin Lee · 2019
Cited alongside, same era.
Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison
Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Chris Chute, Henrik Marklund, Behzad Haghgoo, Robyn L. Ball, Katie S. Shpanskaya, Jayne Seekins, David A. Mong, Safwan S. Halabi, Jesse K. Sandberg, Ricky Jones, David B. Larson, Curtis P. Langlotz, Bhavik N. Patel, Matthew P. Lungren, and Andrew Y. Ng · 2019
Cited alongside, same era.
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Multimodal medical image fusion review: Theoretical background and recent advances
Haithem Hermessi, Olfa Mourali, and Ezzeddine Zagrouba · 2021
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Gloria: A multimodal global-local representation learning framework for label-efficient medical image recognition
Shih-Cheng Huang, Liyue Shen, Matthew P Lungren, and Serena Yeung · 2021
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Mimic-iv-ed
Alistair Johnson, Lucas Bulgarelli, Tom Pollard, Leo Anthony Celi, Roger Mark, and S Horng IV · 2021
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Deep learning for pulmonary embolism detection: tackling the rsna 2020 ai challenge
Ian Pan · 2021
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Deep learning for pulmonary embolism detection on computed tomography pulmonary angiogram: a systematic review and meta-analysis
Shelly Soffer, Eyal Klang, Orit Shimon, Yiftach Barash, Noa Cahan, Hayit Greenspana, and Eli Konen · 2021
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Yuyin Zhou, Shih-Cheng Huang, Jason Alan Fries, Alaa Youssef, Timothy J Amrhein, Marcello Chang, Imon Banerjee, Daniel Rubin, Lei Xing, Nigam Shah, et al · 2021
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A review on multimodal medical image fusion: Compendious analysis of medical modalities, multimodal databases, fusion techniques and quality metrics
Muhammad Adeel Azam, Khan Bahadar Khan, Sana Salahuddin, Eid Rehman, Sajid Ali Khan, Muhammad Attique Khan, Seifedine Kadry, and Amir H Gandomi · 2022
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Automated detection of pulmonary embolism from ct-angiograms using deep learning
Heidi Huhtanen, Mikko Nyman, Tarek Mohsen, Arho Virkki, Antti Karlsson, and Jussi Hirvonen · 2022
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Deep learning and risk assessment in acute pulmonary embolism, 2022
Andetta R Hunsaker · 2022
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Mortality prediction in the icu: The daunting task of predicting the unpredictable
Ajith AK Kumar · 2022
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Clinical-longformer and clinical-bigbird: Transformers for long clinical sequences
Yikuan Li, Ramsey M Wehbe, Faraz S Ahmad, Hanyin Wang, and Yuan Luo · 2022
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A multitask deep learning approach for pulmonary embolism detection and identification
Xiaotian Ma, Emma C Ferguson, Xiaoqian Jiang, Sean I Savitz, and Shayan Shams · 2022
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Multimodal diagnosis for pulmonary embolism from ehr data and ct images
Zhuo Zhi, Moe Elbadawi, Adam Daneshmend, Mine Orlu, Abdul Basit, Andreas Demosthenous, and Miguel Rodrigues · 2022
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The stanford medicine data science ecosystem for clinical and translational research
Alison Callahan, Euan Ashley, Somalee Datta, Priyamvada Desai, Todd A Ferris, Jason A Fries, Michael Halaas, Curtis P Langlotz, Sean Mackey, José D Posada, et al · 2023
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Deep multi-modal fusion of image and non-image data in disease diagnosis and prognosis: a review
Can Cui, Haichun Yang, Yaohong Wang, Shilin Zhao, Zuhayr Asad, Lori A Coburn, Keith T Wilson, Bennett Landman, and Yuankai Huo · 2023
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Omop common data model
OHDSI · 2023
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Self-supervised time-to-event modeling with structured medical records
Ethan Steinberg, Yizhe Xu, Jason Fries, and Nigam Shah · 2023
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