Common Steps in Machine Learning Might Hinder The Explainability Aims in Medicine
Fuente:
arXiv
Enregistré dans:
| Auteur principal: | Salih, Ahmed M |
|---|---|
| Format: | Preprint |
| Publié: |
2024
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
A Fast and Minimal System to Identify Depression Using Smartphones: Explainable Machine Learning-Based Approach
par: Ahmed, Md Sabbir, et autres
Publié: (2025)
par: Ahmed, Md Sabbir, et autres
Publié: (2025)
An Ensemble Framework for Explainable Geospatial Machine Learning Models
par: Liu, Lingbo
Publié: (2024)
par: Liu, Lingbo
Publié: (2024)
Causal Explainability of Machine Learning in Heart Failure Prediction from Electronic Health Records
par: Hou, Yina, et autres
Publié: (2025)
par: Hou, Yina, et autres
Publié: (2025)
Towards Explainable Evaluation Metrics for Machine Translation
par: Leiter, Christoph, et autres
Publié: (2023)
par: Leiter, Christoph, et autres
Publié: (2023)
Measuring What AI Systems Might Do: Towards A Measurement Science in AI
par: Voudouris, Konstantinos, et autres
Publié: (2026)
par: Voudouris, Konstantinos, et autres
Publié: (2026)
MachineLearnAthon: An Action-Oriented Machine Learning Didactic Concept
par: Tkáč, Michal, et autres
Publié: (2024)
par: Tkáč, Michal, et autres
Publié: (2024)
Predicting Male Domestic Violence Using Explainable Ensemble Learning and Exploratory Data Analysis
par: Jahin, Md Abrar, et autres
Publié: (2024)
par: Jahin, Md Abrar, et autres
Publié: (2024)
Machine Learning in Epidemiology
par: Wright, Marvin N., et autres
Publié: (2026)
par: Wright, Marvin N., et autres
Publié: (2026)
Explainable Artificial Intelligence for Dependent Features: Additive Effects of Collinearity
par: Salih, Ahmed M
Publié: (2024)
par: Salih, Ahmed M
Publié: (2024)
An ExplainableFair Framework for Prediction of Substance Use Disorder Treatment Completion
par: Lucas, Mary M., et autres
Publié: (2024)
par: Lucas, Mary M., et autres
Publié: (2024)
Explainable AI for Mental Health Emergency Returns: Integrating LLMs with Predictive Modeling
par: Ahmed, Abdulaziz, et autres
Publié: (2025)
par: Ahmed, Abdulaziz, et autres
Publié: (2025)
Best Practices for Responsible Machine Learning in Credit Scoring
par: Valdrighi, Giovani, et autres
Publié: (2024)
par: Valdrighi, Giovani, et autres
Publié: (2024)
Generative Example-Based Explanations: Bridging the Gap between Generative Modeling and Explainability
par: Vaeth, Philipp, et autres
Publié: (2024)
par: Vaeth, Philipp, et autres
Publié: (2024)
Re-Visiting Explainable AI Evaluation Metrics to Identify The Most Informative Features
par: Salih, Ahmed M.
Publié: (2025)
par: Salih, Ahmed M.
Publié: (2025)
Handling Device Heterogeneity for Deep Learning-based Localization
par: Shokry, Ahmed, et autres
Publié: (2024)
par: Shokry, Ahmed, et autres
Publié: (2024)
Normalise for Fairness: A Simple Normalisation Technique for Fairness in Regression Machine Learning Problems
par: Amin, Mostafa M., et autres
Publié: (2022)
par: Amin, Mostafa M., et autres
Publié: (2022)
Non-Determinism and the Lawlessness of Machine Learning Code
par: Cooper, A. Feder, et autres
Publié: (2022)
par: Cooper, A. Feder, et autres
Publié: (2022)
Insights From Insurance for Fair Machine Learning
par: Fröhlich, Christian, et autres
Publié: (2023)
par: Fröhlich, Christian, et autres
Publié: (2023)
Evaluating Fair Feature Selection in Machine Learning for Healthcare
par: Zawad, Md Rahat Shahriar, et autres
Publié: (2024)
par: Zawad, Md Rahat Shahriar, et autres
Publié: (2024)
Understanding Disparities in Post Hoc Machine Learning Explanation
par: Mhasawade, Vishwali, et autres
Publié: (2024)
par: Mhasawade, Vishwali, et autres
Publié: (2024)
What is Fair? Defining Fairness in Machine Learning for Health
par: Gao, Jianhui, et autres
Publié: (2024)
par: Gao, Jianhui, et autres
Publié: (2024)
Identities are not Interchangeable: The Problem of Overgeneralization in Fair Machine Learning
par: Wang, Angelina
Publié: (2025)
par: Wang, Angelina
Publié: (2025)
Investigating Role of Personal Factors in Shaping Responses to Active Shooter Incident using Machine Learning
par: Liu, Ruying, et autres
Publié: (2025)
par: Liu, Ruying, et autres
Publié: (2025)
Unfair Utilities and First Steps Towards Improving Them
par: Jørgensen, Frederik Hytting, et autres
Publié: (2023)
par: Jørgensen, Frederik Hytting, et autres
Publié: (2023)
Explainability through uncertainty: Trustworthy decision-making with neural networks
par: Thuy, Arthur, et autres
Publié: (2024)
par: Thuy, Arthur, et autres
Publié: (2024)
The SERENADE project: Sensor-Based Explainable Detection of Cognitive Decline
par: Civitarese, Gabriele, et autres
Publié: (2025)
par: Civitarese, Gabriele, et autres
Publié: (2025)
A Human-Centric Approach to Explainable AI for Personalized Education
par: Swamy, Vinitra
Publié: (2025)
par: Swamy, Vinitra
Publié: (2025)
Machine Learning Algorithms for Detecting Mental Stress in College Students
par: Singh, Ashutosh, et autres
Publié: (2024)
par: Singh, Ashutosh, et autres
Publié: (2024)
AdapFair: Ensuring Adaptive Fairness for Machine Learning Operations
par: Huang, Yinghui, et autres
Publié: (2024)
par: Huang, Yinghui, et autres
Publié: (2024)
The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning
par: Fawkes, Jake, et autres
Publié: (2024)
par: Fawkes, Jake, et autres
Publié: (2024)
Interpretable Machine Learning for Resource Allocation with Application to Ventilator Triage
par: Grand-Clément, Julien, et autres
Publié: (2021)
par: Grand-Clément, Julien, et autres
Publié: (2021)
Counterfactual Fairness Evaluation of Machine Learning Models on Educational Datasets
par: Kim, Woojin, et autres
Publié: (2025)
par: Kim, Woojin, et autres
Publié: (2025)
Procedural Fairness and Its Relationship with Distributive Fairness in Machine Learning
par: Wang, Ziming, et autres
Publié: (2025)
par: Wang, Ziming, et autres
Publié: (2025)
The Effect of Enforcing Fairness on Reshaping Explanations in Machine Learning Models
par: Anderson, Joshua Wolff, et autres
Publié: (2025)
par: Anderson, Joshua Wolff, et autres
Publié: (2025)
Towards Public Administration Research Based on Interpretable Machine Learning
par: Liu, Zhanyu, et autres
Publié: (2026)
par: Liu, Zhanyu, et autres
Publié: (2026)
Machine Learning for Identifying Potential Participants in Uruguayan Social Programs
par: Curti, Christian Beron, et autres
Publié: (2025)
par: Curti, Christian Beron, et autres
Publié: (2025)
Transfer Learning and Machine Learning for Training Five Year Survival Prognostic Models in Early Breast Cancer
par: Pilgram, Lisa, et autres
Publié: (2025)
par: Pilgram, Lisa, et autres
Publié: (2025)
Optimizing Mastery Learning by Fast-Forwarding Over-Practice Steps
par: Xia, Meng, et autres
Publié: (2025)
par: Xia, Meng, et autres
Publié: (2025)
Designing an Intelligent Parcel Management System using IoT & Machine Learning
par: Gupta, Mohit, et autres
Publié: (2024)
par: Gupta, Mohit, et autres
Publié: (2024)
The Impact of Machine Learning on Society: An Analysis of Current Trends and Future Implications
par: Siam, Md Kamrul Hossain, et autres
Publié: (2024)
par: Siam, Md Kamrul Hossain, et autres
Publié: (2024)
Documents similaires
-
A Fast and Minimal System to Identify Depression Using Smartphones: Explainable Machine Learning-Based Approach
par: Ahmed, Md Sabbir, et autres
Publié: (2025) -
An Ensemble Framework for Explainable Geospatial Machine Learning Models
par: Liu, Lingbo
Publié: (2024) -
Causal Explainability of Machine Learning in Heart Failure Prediction from Electronic Health Records
par: Hou, Yina, et autres
Publié: (2025) -
Towards Explainable Evaluation Metrics for Machine Translation
par: Leiter, Christoph, et autres
Publié: (2023) -
Measuring What AI Systems Might Do: Towards A Measurement Science in AI
par: Voudouris, Konstantinos, et autres
Publié: (2026)