Feng Xie - Dissemin

All papers authored by Feng Xie

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2024 Marc Ghanem

, Camilo Espinosa, Philip Chung, Momsen Reincke, Natasha Harrison, Thanaphong Phongpreecha, Sayane Shome, Geetha Saarunya, Eloise Berson, Tomin James, Feng Xie

, Chi-Hung Shu, Debapriya Hazra, Samson Mataraso, Yeasul Kim and 11 other authors

Comprehensive overview of the anesthesiology research landscape: A machine Learning Analysis of 737 NIH-funded anesthesiology primary Investigator's publication trends

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Jae Yong Yu, Doyeop Kim, Sunyoung Yoon, Taerim Kim, SeJin Heo, Hansol Chang, Gab Soo Han, Kyung Won Jeong, Rae Woong Park, Jun Myung Gwon, Feng Xie

, Marcus Eng Hock Ong, Yih Yng Ng, Hyung Joon Joo, Won Chul Cha

Inter hospital external validation of interpretable machine learning based triage score for the emergency department using common data model

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This paper was not found in any repository, but could be made available legally by the author.

Jae Yong Yu, Sejin Heo, Feng Xie

, Nan Liu, Sun Yung Yoon, Han Sol Chang, Taerim Kim, Se Uk Lee, Marcus Eng Hock Ong, Yih Yng Ng, Sang Do shin, Kentaro Kajino, Wen-Chu Chiang, Won Chul Cha

Corrigendum to “Development and Asian-wide validation of the Grade for Interpretable Field Triage (GIFT) for predicting mortality in pre-hospital patients using the Pan-Asian Trauma Outcomes Study (PATOS)” [The Lancet Regional Health - Western Pacific 34 (2023) 100733]

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This paper was not found in any repository; the policy of its publisher is unknown or unclear.

2023 Sarah Woldemariam, Feng Xie

, Alennie Roldan, Jacquelyn Roger, Alice Tang, Tomiko Oskotsky, Nima Aghaeepour, Michael Eisenberg, Marina Sirota

Leveraging Electronic Medical Records Reveals Comorbidities Significantly Associated With Male Infertility

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Siqi Li

, Yilin Ning

, Marcus Eng Hock Ong, Bibhas Chakraborty

, Chuan Hong, Feng Xie

, Han Yuan, Mingxuan Liu

, Daniel M. Buckland

, Yong Chen, Nan Liu

FedScore: A privacy-preserving framework for federated scoring system development

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Siqi Li, Pinyan Liu, Gustavo G. Nascimento, Xinru Wang, Fabio Renato Manzolli Leite, Bibhas Chakraborty, Chuan Hong, Yilin Ning, Feng Xie

, Zhen Ling Teo, Daniel Shu Wei Ting, Hamed Haddadi, Marcus Eng Hock Ong, Marco Aurélio Peres, Nan Liu

Federated and distributed learning applications for electronic health records and structured medical data: a scoping review

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Mingxuan Liu, Siqi Li, Han Yuan, Ong Meh, Marcus Eng Hock Ong, Yilin Ning, Feng Xie

, Seyed Ehsan Saffari, Saffari Se, Yuqing Shang, Victor Volovici, Bibhas Chakraborty, Nan Liu

Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques

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Feng Xie

, Yilin Ning, Mingxuan Liu, Siqi Li, Seyed Ehsan Saffari, Saffari Se, Han Yuan, Victor Volovici, Ting Dsw, Daniel Shu Wei Ting, Goldstein Ba, Benjamin Alan Goldstein, Ong Meh, Marcus Eng Hock Ong, Roger Vaughan and 2 other authors

A universal AutoScore framework to develop interpretable scoring systems for predicting common types of clinical outcomes

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Jacquelyn Roger

, Feng Xie

, Jean Costello, Alice Tang, Jay Liu, Tomiko Oskotsky

, Sarah Woldemariam, Idit Kosti, Brian Le, Michael P. Snyder, Linda C. Giudice, Dara Torgerson, Gary M. Shaw, David K. Stevenson, Aleksandar Rajkovic and 6 other authors

Leveraging electronic health records to identify risk factors for recurrent pregnancy loss across two medical centers: a case-control study

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Jae Yong Yu

, Sejin Heo, Feng Xie

, Nan Liu

, Sun Yung Yoon, Han Sol Chang, Taerim Kim, Se Uk Lee, Marcus Eng Hock Ong, Marcus Eng Hock Ong, Yih Yng Ng, Sang Do shin, Sang Do Shin, Kentaro Kajino, Won Chul Cha

Development and Asian-wide validation of the Grade for Interpretable Field Triage (GIFT) for predicting mortality in pre-hospital patients using the Pan-Asian Trauma Outcomes Study (PATOS)

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2022 Seyed Ehsan Saffari, Saffari Se, Yilin Ning, Feng Xie

, Bibhas Chakraborty, Victor Volovici, Roger Vaughan, Nan Liu

, Marcus Eng Hock Ong, Ong Meh

AutoScore-Ordinal: an interpretable machine learning framework for generating scoring models for ordinal outcomes

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Feng Xie

, Jun Zhou, Jin Wee Lee, Mingrui Tan, Siqi Li, Logasan S/O Rajnthern, Marcel Lucas Chee, Bibhas Chakraborty, An-Kwok Ian Wong, Alon Dagan, Marcus Eng Hock Ong, Fei Gao, Nan Liu

Benchmarking emergency department prediction models with machine learning and public electronic health records

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Nan Liu

, Jae Yong Yu, Feng Xie

, Sunyoung Yoon, Marcus Eng Hock Ong, Yih Yng Ng, Won Chul Cha

An external validation study of the Score for Emergency Risk Prediction (SERP), an interpretable machine learning-based triage score for the emergency department

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Maehanyi Frances Rajendram, Faraz Zarisfi, Feng Xie

, Nur Shahidah, Pin Pek, Jun Wei Yeo, Benjamin Yong-Qiang Tan, Matthew Ma, Sang Do Shin, Hideharu Tanaka, Marcus Eng Hock Ong, Nan Liu

, Andrew Fu Wah Ho

External validation of the Survival After ROSC in Cardiac Arrest (SARICA) score for predicting survival after return of spontaneous circulation using multinational pan-asian cohorts

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Yilin Ning

, Siqi Li

, Marcus Eng Hock Ong

, Feng Xie

, Bibhas Chakraborty

, Daniel Shu Wei Ting, Nan Liu

A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort study

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Yukai Ang, Siqi Li, Marcus Eng Hock Ong, Feng Xie

, Su Hooi Teo, Lina Choong, Riece Koniman, Bibhas Chakraborty, Andrew Fu Wah Ho, Nan Liu

Development and validation of an interpretable clinical score for early identification of acute kidney injury at the emergency department

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Han Yuan, Feng Xie

, Marcus Eng Hock Ong, Yilin Ning, Marcel Lucas Chee, Seyed Ehsan Saffari, Hairil Rizal Abdullah, Benjamin Alan Goldstein, Bibhas Chakraborty, Nan Liu

AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data

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Nan Liu

, Feng Xie

, Fahad Javaid Siddiqui

, Andrew Fu Wah Ho

, Bibhas Chakraborty

, Gayathri Devi Nadarajan

, Kenneth Boon Kiat Tan

, Marcus Eng Hock Ong

Leveraging Large-Scale Electronic Health Records and Interpretable Machine Learning for Clinical Decision Making at the Emergency Department: Protocol for System Development and Validation

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Feng Xie

, Nan Liu

, Linxuan Yan

, Yilin Ning, Ka Keat Lim

, Changlin Gong, Yu Heng Kwan, Andrew Fu Wah Ho, Lian Leng Low, Bibhas Chakraborty, Marcus Eng Hock Ong

Development and validation of an interpretable machine learning scoring tool for estimating time to emergency readmissions

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Feng Xie

, Han Yuan, Yilin Ning, Marcus Eng Hock Ong, Mengling Feng, Wynne Hsu, Bibhas Chakraborty, Nan Liu

Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies

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All papers authored by Feng Xie