Results 31 to 40 of about 78,288 (166)

Carbon price interval prediction by bidirectional long short-term memory and multi-objective optimization with an asymmetric scaling approach

Energy Reports
Accurate carbon price prediction is essential for decision-making and risk management. Most existing predictive models produce deterministic results and fail to account for uncertainties in carbon prices. To address this limitation, this study introduces
Di Sha, Arne Johannssen, Xianyi Zeng, Zhenglei He, Hanhan Wu, Kim Phuc Tran   +5 more
doaj   +1 more source

A Review on Machine Learning Methods for Customer Churn Prediction and Recommendations for Business Practitioners

IEEE Access
Due to market deregulation and globalisation, competitive environments in various sectors continuously evolve, leading to increased customer churn. Effectively anticipating and mitigating customer churn is vital for businesses to retain their customer ...
Awais Manzoor, M. Atif Qureshi, Etain Kidney, Luca Longo   +3 more
doaj   +1 more source

Advancing Deliberative Discourse Measurement: The Intersection with Computational Abstract Argumentation in Discourse Quality Evaluations

Systems
This research investigates the potential of computational argumentation, specifically the application of the Abstract Argumentation Framework (AAF), to enhance the evaluation of deliberative quality in public discourse.
Sanjay Kumar, Jane Suiter, Luca Longo
doaj   +1 more source

Artificial Intelligence and Patient-Centered Decision-Making [PDF]

, 2020
Advanced AI systems are rapidly making their way into medical research and practice, and, arguably, it is only a matter of time before they will surpass human practitioners in terms of accuracy, reliability, and knowledge.
Bjerring, Jens Christian, Busch, Jacob
core  

Exploring the clinical value of concept-based AI explanations in gastrointestinal disease detection

Scientific Reports
Complex artificial intelligence models, like deep neural networks, have shown exceptional capabilities to detect early-stage polyps and tumors in the gastrointestinal tract.
Andrea M. Storås, Maximilian Dreyer, Frederik Pahde, Sebastian Lapuschkin, Wojciech Samek, Pål Halvorsen, Thomas de Lange, Yuichi Mori, Alexander Hann, Tyler M. Berzin, Sravanthi Parasa, Michael A. Riegler   +11 more
doaj   +1 more source

Enhancing Decision Tree based Interpretation of Deep Neural Networks through L1-Orthogonal Regularization

, 2019
One obstacle that so far prevents the introduction of machine learning models primarily in critical areas is the lack of explainability. In this work, a practicable approach of gaining explainability of deep artificial neural networks (NN) using an ...
Huber, Marco F., Maucher, Johannes, Schaaf, Nina   +2 more
core   +1 more source

Explainable Artificial Intelligence in Echocardiography [PDF]

Advanced Ultrasound in Diagnosis and Therapy
Recent advancements in artificial intelligence (AI) have generated novel opportunities and challenges in ultrasound imaging. Deep learning algorithms exhibit significant potential in analyzing echocardiographic images, encompassing tasks such as view ...
Hu Xuelin, Zhu Ye, Zhang Zisang, Quan Yuanting, Chen Wenwen, Chen Leichong, Xu Guangyu, Qin Luning, Xie Mingxing, Zhang Li
doaj   +1 more source

Integrating machine learning algorithms and explainable artificial intelligence approach for predicting patient unpunctuality in psychiatric clinics

Healthcare Analytics, 2023
This study addresses patient unpunctuality, a major concern affecting patient waiting time, resource utilization, and quality of care. We develop and compare four machine learning models, including multinomial logistic regression, decision tree, random ...
Alireza Kasaie, Suchithra Rajendran
doaj   +1 more source

Deterministic Uncertainty Estimation for Multi-Modal Regression With Deep Neural Networks

IEEE Access
Prediction interval (PI) is a common method to represent predictive uncertainty in regression by deep neural networks. This paper proposes an extension of the prediction interval by using a union of disjoint intervals. Since previous PI methods assumed a
Jaehak Cho, Jae Myung Kim, Seungyub Han, Jungwoo Lee   +3 more
doaj   +1 more source

Explainable Artificial Intelligence Applications in Cyber Security: State-of-the-Art in Research

IEEE Access, 2022
This survey presents a comprehensive review of current literature on Explainable Artificial Intelligence (XAI) methods for cyber security applications. Due to the rapid development of Internet-connected systems and Artificial Intelligence in recent years,
Zhibo Zhang, Hussam Al Hamadi, Ernesto Damiani, Chan Yeob Yeun, Fatma Taher   +4 more
doaj   +1 more source