Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model

5 November 2015

Papers citing "Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model"

50 / 244 papers shown

Title
Rationalizing Predictions by Adversarial Information Calibration Lei Sha Oana-Maria Camburu Thomas Lukasiewicz 64 7 0 15 Jan 2023
Towards Reconciling Usability and Usefulness of Explainable AI Methodologies Pradyumna Tambwekar Matthew C. Gombolay 66 8 0 13 Jan 2023
Semantic match: Debugging feature attribution methods in XAI for healthcare Giovanni Cina Tabea E. Rober Rob Goedhart cS. .Ilker Birbil 76 4 0 05 Jan 2023
Explainable AI for Bioinformatics: Methods, Tools, and Applications Md. Rezaul Karim Tanhim Islam Oya Beyan Christoph Lange Michael Cochez Dietrich-Rebholz Schuhmann Stefan Decker 114 78 0 25 Dec 2022
Deep Explainable Learning with Graph Based Data Assessing and Rule Reasoning Yuanlong Li Gaopan Huang Min Zhou Chuan Fu Honglin Qiao Yan He 71 1 0 09 Nov 2022
Learning to Advise Humans in High-Stakes Settings Nicholas Wolczynski M. Saar-Tsechansky Tong Wang 53 0 0 23 Oct 2022
Self-explaining deep models with logic rule reasoning Seungeon Lee Xiting Wang Sungwon Han Xiaoyuan Yi Xing Xie M. Cha NAI ReLM LRM 92 17 0 13 Oct 2022
Why we do need Explainable AI for Healthcare Giovanni Cina Tabea E. Rober Rob Goedhart Ilker Birbil 71 14 0 30 Jun 2022
OpenXAI: Towards a Transparent Evaluation of Model Explanations Chirag Agarwal Dan Ley Satyapriya Krishna Eshika Saxena Martin Pawelczyk Nari Johnson Isha Puri Marinka Zitnik Himabindu Lakkaraju XAI 136 147 0 22 Jun 2022
A Human-Centric Take on Model Monitoring Murtuza N. Shergadwala Himabindu Lakkaraju K. Kenthapadi 91 11 0 06 Jun 2022
bsnsing: A decision tree induction method based on recursive optimal boolean rule composition Yan-ching Liu 67 10 0 30 May 2022
Analyzing Tree Architectures in Ensembles via Neural Tangent Kernel Ryuichi Kanoh M. Sugiyama 142 2 0 25 May 2022
ExMo: Explainable AI Model using Inverse Frequency Decision Rules Pradip Mainali I. Psychoula F. Petitcolas 29 0 0 20 May 2022
Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations Jessica Dai Sohini Upadhyay Ulrich Aïvodji Stephen H. Bach Himabindu Lakkaraju 92 58 0 15 May 2022
Efficient Learning of Interpretable Classification Rules Bishwamittra Ghosh Dmitry Malioutov Kuldeep S. Meel 64 8 0 14 May 2022
Bayes Point Rule Set Learning F. Aiolli Luca Bergamin Tommaso Carraro Mirko Polato 51 0 0 11 Apr 2022
Modern Views of Machine Learning for Precision Psychiatry Z. Chen Prathamesh Kulkarni Kulkarni I. Galatzer-Levy Benedetta Bigio C. Nasca Yu Zhang 76 103 0 04 Apr 2022
Innovations in trigger and data acquisition systems for next-generation physics facilities R. Bartoldus C. Bernius David W. Miller AI4CE 29 8 0 15 Mar 2022
Making use of supercomputers in financial machine learning Philippe Cotte P. Lagier Vincent Margot Christoph F. Geißler 46 2 0 01 Mar 2022
Deep Learning, Natural Language Processing, and Explainable Artificial Intelligence in the Biomedical Domain M. Moradi Matthias Samwald 132 8 0 25 Feb 2022
Learning Interpretable, High-Performing Policies for Autonomous Driving Rohan R. Paleja Yaru Niu Andrew Silva Chace Ritchie Sugju Choi Matthew C. Gombolay 87 17 0 04 Feb 2022
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective Satyapriya Krishna Tessa Han Alex Gu Steven Wu S. Jabbari Himabindu Lakkaraju 284 197 0 03 Feb 2022
Hierarchical Shrinkage: improving the accuracy and interpretability of tree-based methods Abhineet Agarwal Yan Shuo Tan Omer Ronen Chandan Singh Bin Yu 90 27 0 02 Feb 2022
Describing Differences between Text Distributions with Natural Language Ruiqi Zhong Charles Burton Snell Dan Klein Jacob Steinhardt VLM 198 44 0 28 Jan 2022
Fast Interpretable Greedy-Tree Sums Yan Shuo Tan Chandan Singh Keyan Nasseri Abhineet Agarwal James Duncan Omer Ronen M. Epland Aaron E. Kornblith Bin Yu AI4CE 82 8 0 28 Jan 2022
Visual Exploration of Machine Learning Model Behavior with Hierarchical Surrogate Rule Sets Jun Yuan Brian Barr Kyle Overton E. Bertini 45 11 0 19 Jan 2022
FROTE: Feedback Rule-Driven Oversampling for Editing Models Öznur Alkan Dennis L. Wei Massimiliano Mattetti Rahul Nair Elizabeth M. Daly Diptikalyan Saha 35 8 0 04 Jan 2022
Towards Relatable Explainable AI with the Perceptual Process Wencan Zhang Brian Y. Lim AAML XAI 89 66 0 28 Dec 2021
Multiclass Optimal Classification Trees with SVM-splits V. Blanco Alberto Japón J. Puerto 55 6 0 16 Nov 2021
Interpretable and Fair Boolean Rule Sets via Column Generation Connor Lawless S. Dash Oktay Gunluk Dennis L. Wei FaML 101 13 0 16 Nov 2021
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds Yan Shuo Tan Abhineet Agarwal Bin Yu 79 11 0 18 Oct 2021
Scalable Rule-Based Representation Learning for Interpretable Classification Zhuo Wang Wei Zhang Ning Liu Jianyong Wang 79 63 0 30 Sep 2021
An Exploration And Validation of Visual Factors in Understanding Classification Rule Sets Jun Yuan O. Nov E. Bertini 50 10 0 19 Sep 2021
Towards Out-Of-Distribution Generalization: A Survey Jiashuo Liu Zheyan Shen Yue He Xingxuan Zhang Renzhe Xu Han Yu Peng Cui CML OOD 168 536 0 31 Aug 2021
Improving Human Sequential Decision-Making with Reinforcement Learning Hamsa Bastani Osbert Bastani W. Sinchaisri HAI OffRL 83 13 0 19 Aug 2021
Interpreting and improving deep-learning models with reality checks Chandan Singh Wooseok Ha Bin Yu FAtt 84 3 0 16 Aug 2021
Logic Explained Networks Gabriele Ciravegna Pietro Barbiero Francesco Giannini Marco Gori Pietro Lio Marco Maggini S. Melacci 90 70 0 11 Aug 2021
Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutions Eike Petersen Yannik Potdevin Esfandiar Mohammadi Stephan Zidowitz Sabrina Breyer ... Sandra Henn Ludwig Pechmann M. Leucker P. Rostalski Christian Herzog FaML AILaw OOD 105 23 0 20 Jul 2021
Fair Decision Rules for Binary Classification Connor Lawless Oktay Gunluk FaML 50 6 0 03 Jul 2021
Feature Attributions and Counterfactual Explanations Can Be Manipulated Dylan Slack Sophie Hilgard Sameer Singh Himabindu Lakkaraju FAtt 34 6 0 23 Jun 2021
Interpretable Machine Learning Classifiers for Brain Tumour Survival Prediction C. Charlton M. Poon P. Brennan Jacques D. Fleuriot 26 0 0 17 Jun 2021
Entropy-based Logic Explanations of Neural Networks Pietro Barbiero Gabriele Ciravegna Francesco Giannini Pietro Lio Marco Gori S. Melacci FAtt XAI 93 80 0 12 Jun 2021
When and Why does a Model Fail? A Human-in-the-loop Error Detection Framework for Sentiment Analysis Zhe Liu Yufan Guo J. Mahmud 82 10 0 02 Jun 2021
An exact counterfactual-example-based approach to tree-ensemble models interpretability P. Blanchart 60 4 0 31 May 2021
Analysis and classification of main risk factors causing stroke in Shanxi Province Junjie Liu Yiyang Sun Jing Ma Jiachen Tu Yuhui Deng Ping He Huaxiong Huang Xiaoshuang Zhou Shixin Xú 27 0 0 29 May 2021
Explainable Activity Recognition for Smart Home Systems Devleena Das Yasutaka Nishimura R. Vivek Naoto Takeda Sean T. Fish Thomas Ploetz Sonia Chernova 45 43 0 20 May 2021
Information-theoretic Evolution of Model Agnostic Global Explanations Sukriti Verma Nikaash Puri Piyush B. Gupta Balaji Krishnamurthy FAtt 62 0 0 14 May 2021
On Guaranteed Optimal Robust Explanations for NLP Models Emanuele La Malfa A. Zbrzezny Rhiannon Michelmore Nicola Paoletti Marta Z. Kwiatkowska FAtt 77 48 0 08 May 2021
Towards an Interpretable Data-driven Trigger System for High-throughput Physics Facilities C. Mahesh Kristin Dona David W. Miller Yuxin Chen AI4CE 48 2 0 14 Apr 2021
Model Learning with Personalized Interpretability Estimation (ML-PIE) M. Virgolin A. D. Lorenzo Francesca Randone Eric Medvet M. Wahde 101 31 0 13 Apr 2021