Explainable AI methods-a brief overview

A Holzinger, A Saranti, C Molnar, P Biecek… - … workshop on extending …, 2020 - Springer
Abstract Explainable Artificial Intelligence (xAI) is an established field with a vibrant
community that has developed a variety of very successful approaches to explain and …

Artificial intelligence ethics and challenges in healthcare applications: a comprehensive review in the context of the European GDPR mandate

M Mohammad Amini, M Jesus… - Machine Learning and …, 2023 - mdpi.com
This study examines the ethical issues surrounding the use of Artificial Intelligence (AI) in
healthcare, specifically nursing, under the European General Data Protection Regulation …

[HTML][HTML] Fairness and explanation in AI-informed decision making

A Angerschmid, J Zhou, K Theuermann… - Machine Learning and …, 2022 - mdpi.com
AI-assisted decision-making that impacts individuals raises critical questions about
transparency and fairness in artificial intelligence (AI). Much research has highlighted the …

Impact of generative artificial intelligence models on the performance of citizen data scientists in retail firms

RA Abumalloh, M Nilashi, KB Ooi, GWH Tan… - Computers in …, 2024 - Elsevier
Abstract Generative Artificial Intelligence (AI) models serve as powerful tools for
organizations aiming to integrate advanced data analysis and automation into their …

The next frontier: AI we can really trust

A Holzinger - Joint European conference on machine learning and …, 2021 - Springer
Enormous advances in the domain of statistical machine learning, the availability of large
amounts of training data, and increasing computing power have made Artificial Intelligence …

AI and professional liability assessment in healthcare. A revolution in legal medicine?

C Terranova, C Cestonaro, L Fava, A Cinquetti - Frontiers in Medicine, 2024 - frontiersin.org
The adoption of advanced artificial intelligence (AI) systems in healthcare is transforming the
healthcare-delivery landscape. Artificial intelligence may enhance patient safety and …

[HTML][HTML] Resilient artificial intelligence in health: synthesis and research agenda toward next-generation trustworthy clinical decision support

C Sáez, P Ferri, JM García-Gómez - Journal of Medical Internet Research, 2024 - jmir.org
Artificial intelligence (AI)–based clinical decision support systems are gaining momentum by
relying on a greater volume and variety of secondary use data. However, the uncertainty …

[HTML][HTML] Actionable explainable AI (AxAI): a practical example with aggregation functions for adaptive classification and textual explanations for interpretable machine …

A Saranti, M Hudec, E Mináriková, Z Takáč… - Machine Learning and …, 2022 - mdpi.com
In many domains of our daily life (eg, agriculture, forestry, health, etc.), both laymen and
experts need to classify entities into two binary classes (yes/no, good/bad …

Cervical cancer survival prediction by machine learning algorithms: a systematic review

M Rahimi, A Akbari, F Asadi, H Emami - BMC cancer, 2023 - Springer
Background Cervical cancer is a common malignant tumor of the female reproductive
system and is considered a leading cause of mortality in women worldwide. The analysis of …

[HTML][HTML] On relevant features for the recurrence prediction of urothelial carcinoma of the bladder

L Schwarz, D Sobania, F Rothlauf - International Journal of Medical …, 2024 - Elsevier
Background Urothelial bladder cancer (UBC) is characterized by a high recurrence rate,
which is predicted by scoring systems. However, recent studies show the superiority of …