Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models

27 April 2020

Papers citing "Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models"

6 / 6 papers shown

Title
Learn-By-Calibrating: Using Calibration as a Training Objective Jayaraman J. Thiagarajan Bindya Venkatesh Deepta Rajan UQCV 37 6 0 30 Oct 2019
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques Vijay Arya Rachel K. E. Bellamy Pin-Yu Chen Amit Dhurandhar Michael Hind ... Karthikeyan Shanmugam Moninder Singh Kush R. Varshney Dennis L. Wei Yunfeng Zhang XAI 62 392 0 06 Sep 2019
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use S. Tonekaboni Shalmali Joshi M. Mccradden Anna Goldenberg 65 391 0 13 May 2019
Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC) Noel Codella V. Rotemberg P. Tschandl M. E. Celebi Stephen W. Dusza ... Aadi Kalloo Konstantinos Liopyris Michael Marchetti Harald Kittler Allan Halpern 97 1,184 0 09 Feb 2019
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 120 3,938 0 06 Feb 2018
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 278 2,262 0 24 Jun 2017