A causal perspective on dataset bias in machine learning for medical imaging
As machine learning methods gain prominence within clinical decision-making, the need to
address fairness concerns becomes increasingly urgent. Despite considerable work …
address fairness concerns becomes increasingly urgent. Despite considerable work …
Predicting non-muscle invasive bladder cancer outcomes using artificial intelligence: a systematic review using APPRAISE-AI
Accurate prediction of recurrence and progression in non-muscle invasive bladder cancer
(NMIBC) is essential to inform management and eligibility for clinical trials. Despite …
(NMIBC) is essential to inform management and eligibility for clinical trials. Despite …
TRIPOD+ AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual
Prognosis Or Diagnosis) statement was published in 2015 to provide the minimum reporting …
Prognosis Or Diagnosis) statement was published in 2015 to provide the minimum reporting …
Development and preliminary testing of Health Equity Across the AI Lifecycle (HEAAL): A framework for healthcare delivery organizations to mitigate the risk of AI …
JY Kim, A Hasan, KC Kellogg, W Ratliff… - PLOS Digital …, 2024 - journals.plos.org
The use of data-driven technologies such as Artificial Intelligence (AI) and Machine Learning
(ML) is growing in healthcare. However, the proliferation of healthcare AI tools has outpaced …
(ML) is growing in healthcare. However, the proliferation of healthcare AI tools has outpaced …
No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging
As machine learning methods gain prominence within clinical decision-making, addressing
fairness concerns becomes increasingly urgent. Despite considerable work dedicated to …
fairness concerns becomes increasingly urgent. Despite considerable work dedicated to …
[PDF][PDF] A normative framework for artificial intelligence as a sociotechnical system in healthcare
Artificial intelligence (AI) tools are of great interest to healthcare organizations for their
potential to improve patient care, yet their translation into clinical settings remains …
potential to improve patient care, yet their translation into clinical settings remains …
Designing Guiding Principles for NLP for Healthcare: A Case Study of Maternal Health
Objective: An ethical framework for the use of large language models (LLMs) is urgently
needed to shape how natural language processing (NLP) tools are used for healthcare …
needed to shape how natural language processing (NLP) tools are used for healthcare …
[PDF][PDF] NLP for Maternal Healthcare: Perspectives and Guiding Principles in the Age of LLMs
Ethical frameworks for the use of natural language processing (NLP) are urgently needed to
shape how large language models (LLMs) and similar tools are used for healthcare …
shape how large language models (LLMs) and similar tools are used for healthcare …
Towards Explainable Artificial Intelligence (XAI): A Data Mining Perspective
Given the complexity and lack of transparency in deep neural networks (DNNs), extensive
efforts have been made to make these systems more interpretable or explain their behaviors …
efforts have been made to make these systems more interpretable or explain their behaviors …
Ensuring Trustworthy Machine Learning: Ethical Foundations, Robust Algorithms, and Responsible Applications
UA Usmani, AY Usmani… - … Conference on Computing …, 2023 - ieeexplore.ieee.org
Intrusion detection, a pivotal facet of securing digital environments, intersects with the
proliferation of machine learning (ML) technologies, which have driven transformative …
proliferation of machine learning (ML) technologies, which have driven transformative …