MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning
Models on MIMIC-IV Dataset

MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset

12 February 2021

Papers citing "MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset"

15 / 15 papers shown

Title
Explainable AI for clinical risk prediction: a survey of concepts, methods, and modalities Munib Mesinovic Peter Watkinson Ting Zhu FaML 19 3 0 16 Aug 2023
MLHOps: Machine Learning for Healthcare Operations Kristoffer Larsen Vallijah Subasri A. Krishnan Cláudio Tinoco Mesquita Diana Paez Laleh Seyyed-Kalantari Amalia Peix LM&MA AI4TS VLM 27 2 0 04 May 2023
Uncovering Bias in Personal Informatics Sofia Yfantidou Pavlos Sermpezis Athena Vakali R. Baeza-Yates 24 6 0 27 Mar 2023
Sampling Through the Lens of Sequential Decision Making J. Dou Alvin Pan Runxue Bao Haiyi Mao Lei Luo Zhi-Hong Mao 26 19 0 17 Aug 2022
Fair Machine Learning in Healthcare: A Review Qizhang Feng Mengnan Du Na Zou Xia Hu FaML 30 0 0 29 Jun 2022
Integrated multimodal artificial intelligence framework for healthcare applications L. Soenksen Yu Ma C. Zeng L. Boussioux Kimberly Villalobos Carballo Liangyuan Na H. Wiberg Michael Lingzhi Li Ignacio Fuentes Dimitris Bertsimas 28 151 0 25 Feb 2022
A Consistent and Efficient Evaluation Strategy for Attribution Methods Yao Rong Tobias Leemann V. Borisov Gjergji Kasneci Enkelejda Kasneci FAtt 23 92 0 01 Feb 2022
Consolidated learning -- a domain-specific model-free optimization strategy with examples for XGBoost and MIMIC-IV Katarzyna Wo'znica Mateusz Grzyb Zuzanna Trafas P. Biecek 68 2 0 27 Jan 2022
Unsupervised Learning to Subphenotype Delirium Patients from Electronic Health Records Yiqing Zhao Yuan Luo 9 2 0 31 Oct 2021
Algorithm Fairness in AI for Medicine and Healthcare Richard J. Chen Tiffany Y. Chen Jana Lipkova Judy J. Wang Drew F. K. Williamson Ming Y. Lu S. Sahai Faisal Mahmood FaML 73 45 0 01 Oct 2021
Synthetic Benchmarks for Scientific Research in Explainable Machine Learning Yang Liu Sujay Khandagale Colin White W. Neiswanger 34 65 0 23 Jun 2021
Pitfalls of Explainable ML: An Industry Perspective Sahil Verma Aditya Lahiri John P. Dickerson Su-In Lee XAI 13 9 0 14 Jun 2021
AMMU : A Survey of Transformer-based Biomedical Pretrained Language Models Katikapalli Subramanyam Kalyan A. Rajasekharan S. Sangeetha LM&MA MedIm 20 164 0 16 Apr 2021
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 323 4,203 0 23 Aug 2019
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 251 3,683 0 28 Feb 2017