A sociotechnical view of algorithmic fairness
M Dolata, S Feuerriegel… - Information Systems …, 2022 - Wiley Online Library
Algorithmic fairness (AF) has been framed as a newly emerging technology that mitigates
systemic discrimination in automated decision‐making, providing opportunities to improve …
systemic discrimination in automated decision‐making, providing opportunities to improve …
Ethics & AI: A systematic review on ethical concerns and related strategies for designing with AI in healthcare
In modern life, the application of artificial intelligence (AI) has promoted the implementation
of data-driven algorithms in high-stakes domains, such as healthcare. However, it is …
of data-driven algorithms in high-stakes domains, such as healthcare. However, it is …
The limits of fair medical imaging AI in real-world generalization
As artificial intelligence (AI) rapidly approaches human-level performance in medical
imaging, it is crucial that it does not exacerbate or propagate healthcare disparities. Previous …
imaging, it is crucial that it does not exacerbate or propagate healthcare disparities. Previous …
[HTML][HTML] Significance of machine learning in healthcare: Features, pillars and applications
Abstract Machine Learning (ML) applications are making a considerable impact on
healthcare. ML is a subtype of Artificial Intelligence (AI) technology that aims to improve the …
healthcare. ML is a subtype of Artificial Intelligence (AI) technology that aims to improve the …
Algorithmic fairness in computational medicine
Machine learning models are increasingly adopted for facilitating clinical decision-making.
However, recent research has shown that machine learning techniques may result in …
However, recent research has shown that machine learning techniques may result in …
Covid-19 and computer audition: An overview on what speech & sound analysis could contribute in the sars-cov-2 corona crisis
At the time of writing this article, the world population is suffering from more than 2 million
registered COVID-19 disease epidemic-induced deaths since the outbreak of the corona …
registered COVID-19 disease epidemic-induced deaths since the outbreak of the corona …
Improving the fairness of chest x-ray classifiers
Deep learning models have reached or surpassed human-level performance in the field of
medical imaging, especially in disease diagnosis using chest x-rays. However, prior work …
medical imaging, especially in disease diagnosis using chest x-rays. However, prior work …
Towards automated urban planning: When generative and chatgpt-like ai meets urban planning
The two fields of urban planning and artificial intelligence (AI) arose and developed
separately. However, there is now cross-pollination and increasing interest in both fields to …
separately. However, there is now cross-pollination and increasing interest in both fields to …
[PDF][PDF] A Comprehensive Survey of Machine Learning in Healthcare: Predicting Heart and Liver Disease, Tuberculosis Detection in Chest X-Ray Images
C Banapuram, AC Naik, MK Vanteru, VS Kumar… - … International Journal of …, 2024 - gnits.ac.in
The utilization of Machine Learning (ML) has become widespread across several
disciplines. ML is utilized as an effective support mechanism in clinical diagnostics due to …
disciplines. ML is utilized as an effective support mechanism in clinical diagnostics due to …
Foundation metrics for evaluating effectiveness of healthcare conversations powered by generative AI
Abstract Generative Artificial Intelligence is set to revolutionize healthcare delivery by
transforming traditional patient care into a more personalized, efficient, and proactive …
transforming traditional patient care into a more personalized, efficient, and proactive …