Anne Mottram

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All published works

Action	Title	Year	Authors
+ PDF Chat	Learning to Select the Best Forecasting Tasks for Clinical Outcome Prediction	2024	Yuan Xue Nan Du Anne Mottram Martin Seneviratne Andrew M. Dai
+	Concept-based model explanations for electronic health records	2021	Diana Mincu Eric Loreaux Shaobo Hou Sebastien Baur Ivan Protsyuk Martin Seneviratne Anne Mottram Nenad Tomašev Alan Karthikesalingam Jessica Schrouff

Common Coauthors

Coauthor	Papers Together
Martin Seneviratne	2
Jessica Schrouff	1
Yuan Xue	1
Andrew M. Dai	1
Diana Mincu	1
Eric Loreaux	1
Nenad Tomašev	1
Ivan Protsyuk	1
Sebastien Baur	1
Nan Du	1
Alan Karthikesalingam	1
Shaobo Hou	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Learning to Diagnose with LSTM Recurrent Neural Networks	2015	Zachary C. Lipton David C. Kale Charles Elkan Randall C. Wetzel	1
+	RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism	2016	Edward Choi Mohammad Taha Bahadori Joshua A. Kulas Andy Schuetz Walter F. Stewart Jimeng Sun	1
+	Axiomatic Attribution for Deep Networks	2017	Mukund Sundararajan Ankur Taly Qiqi Yan	1
+	An Improved Multi-Output Gaussian Process RNN with Real-Time Validation for Early Sepsis Detection	2017	Joseph Futoma Sanjay Hariharan Mark Sendak Nathan Brajer Meredith E. Clement Armando Bedoya Cara O’Brien Katherine Heller	1
+	Attend and Diagnose: Clinical Time Series Analysis using Attention Models	2017	Huan Song Deepta Rajan Jayaraman J. Thiagarajan Andreas Spanias	1
+	A unified view of gradient-based attribution methods for Deep Neural Networks	2017	Marco Ancona Enea Ceolini Cengiz Öztireli Markus Groß	1
+	What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use	2019	Sana Tonekaboni Shalmali Joshi Melissa D. McCradden Anna Goldenberg	1
+	Axiomatic Attribution for Deep Networks	2017	Mukund Sundararajan Ankur Taly Qiqi Yan	1
+	Counterfactual Reasoning for Fair Clinical Risk Prediction.	2019	Stephen Pfohl Tony Duan Daisy Yi Ding Nigam H. Shah	1
+	Explaining Classifiers with Causal Concept Effect (CaCE)	2019	Yash Goyal Amir Feder Uri Shalit Been Kim	1
+	Explaining an increase in predicted risk for clinical alerts	2019	Michaela Hardt Alvin Rajkomar Gerardo Flores Andrew M. Dai Michael Howell Greg S. Corrado Claire Cui Moritz Hardt	1
+	Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps	2013	Karen Simonyan Andrea Vedaldi Andrew Zisserman	1
+	Learning to Diagnose with LSTM Recurrent Neural Networks	2015	Zachary C. Lipton David C. Kale Charles Elkan Randall Wetzell	1
+	RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism	2016	Edward Choi Mohammad Taha Bahadori Jimeng Sun Joshua A. Kulas Andy Schuetz Walter F. Stewart	1
+	Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)	2017	Been Kim Martin Wattenberg Justin Gilmer Carrie J. Cai James Wexler Fernanda Viégas Rory Sayres	1
+ PDF Chat	Attend and Diagnose: Clinical Time Series Analysis Using Attention Models	2018	Huan Song Deepta Rajan Jayaraman J. Thiagarajan Andreas Spanias	1
+	Explanation by Progressive Exaggeration	2019	Sumedha Singla Brian P. Pollack Junxiang Chen Kayhan Batmanghelich	1
+	On Completeness-aware Concept-Based Explanations in Deep Neural Networks.	2019	Chih‐Kuan Yeh Been Kim Sercan Ö. Arık Chun‐Liang Li Tomas Pfister Pradeep Ravikumar	1
+	Explaining an increase in predicted risk for clinical alerts	2020	Michaela Hardt Alvin Rajkomar Gerardo Flores Andrew M. Dai Michael D. Howell Greg S. Corrado Claire Cui Moritz Hardt	1
+ PDF Chat	Scalable and accurate deep learning with electronic health records	2018	Alvin Rajkomar Eyal Oren Kai Chen Andrew M. Dai Nissan Hajaj Michaela Hardt Peter J. Liu Xiaobing Liu Jake Marcus Mimi Sun	1
+ PDF Chat	DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning	2019	Benjamin Shickel Tyler J. Loftus Lasith Adhikari Tezcan Ozrazgat‐Baslanti Azra Bihorac Parisa Rashidi	1
+	Temporal pointwise convolutional networks for length of stay prediction in the intensive care unit	2021	Emma Rocheteau Píetro Lió Stephanie L. Hyland	1
+	Explanation by Progressive Exaggeration	2019	Sumedha Singla Brian Pollack Junxiang Chen Kayhan Batmanghelich	1
+	Counterfactual Reasoning for Fair Clinical Risk Prediction	2019	Stephen Pfohl Tony Duan Daisy Yi Ding Nigam H. Shah	1
+	An Improved Multi-Output Gaussian Process RNN with Real-Time Validation for Early Sepsis Detection	2017	Joseph Futoma Sanjay Hariharan Mark Sendak Nathan Brajer Meredith E. Clement Armando Bedoya Cara O’Brien Katherine Heller	1
+	Towards better understanding of gradient-based attribution methods for Deep Neural Networks	2017	Marco Ancona Enea Ceolini Cengiz Öztireli Markus Groß	1