Results 81 to 90 of about 23,034 (235)

Regulating Explainable Artificial Intelligence (XAI) May Harm Consumers

Marketing Science
This work analyzes the impact of regulating explainable artificial intelligence.
Behnam Mohammadi, Nikhil Malik, Tim Derdenger, Kannan Srinivasan   +3 more
openaire   +2 more sources

Machine Learning for Predictive Modeling in Nanomedicine‐Based Cancer Drug Delivery

Med Research, EarlyView.
The integration of AI/ML into nanomedicine offers a transformative approach to therapeutic design and optimization. Unlike conventional empirical methods, AI/ML models (such as classification, regression, and neural networks) enable the analysis of complex clinical and formulation datasets to predict optimal nanoparticle characteristics and therapeutic
Rohan Chand Sahu, Sanchit Arora, Dinesh Kumar, Ashish Kumar Agrawal   +3 more
wiley   +1 more source

Transformative impact of explainable artificial intelligence: bridging complexity and trust

Discover Artificial Intelligence
Artificial Intelligence and Deep Learning have gained widespread popularity in all sectors and industries from healthcare to finance and industrial management.
Girish Paliwal, Ashish Kumar, Kanta Prasad Sharma, Deepshika Bhargava, Vijay Mohan Shrimal   +4 more
doaj   +1 more source

eXplainable Artificial Intelligence (XAI) in aging clock models

Ageing Research Reviews
eXplainable Artificial Intelligence (XAI) is a rapidly progressing field of machine learning, aiming to unravel the predictions of complex models. XAI is especially required in sensitive applications, e.g. in health care, when diagnosis, recommendations and treatment choices might rely on the decisions made by artificial intelligence systems.
Alena Kalyakulina, Igor Yusipov, Alexey Moskalev, Claudio Franceschi, Mikhail Ivanchenko   +4 more
openaire   +3 more sources

How AI and Digital Technologies Can Enhance Sustainable Livestock Manure Management: An Overview From Treatment to Distribution

Sustainable Development, EarlyView.
ABSTRACT Sustainable livestock manure management sits at the nexus of climate, nutrient circularity and water quality. This review explores how artificial intelligence (AI) and digital platforms are used across four management stages, that is, treatment, storage, valorisation and distribution, and figures out where integration fails to deliver ...
Zhan Shi, Feihong Liang, Francesco Marinello, Andrea Pezzuolo   +3 more
wiley   +1 more source

Explainable machine learning methods to predict postpartum depression risk

Systems Science & Control Engineering
Postpartum depression (PPD) is a type of depression that mothers have following childbirth due to hormonal changes, psychological transition to parenting, and exhaustion. This depression strikes either during/or in the first year following childbirth. It
Susmita Shivaprasad, Krishnaraj Chadaga, Niranjana Sampathila, Srikanth Prabhu, Rajagopala Chadaga P, Swathi K S   +5 more
doaj   +1 more source

Pixel Lens: A Granular Assessment of Saliency Explanations

Artificial Intelligence for Engineering, EarlyView.
We propose a pipeline that detects shortcut‐dominated classifiers by comparing predictions on clean and shortcut‐perturbed images and checking dominance via a Shapley‐based ground‐truth explainer. The workflow quantifies the explanation quality of different explainable artificial intelligence (XAI) methods.
Kanglong Fan, Chen Ma, Yifan Peng, Jinglong Yang, Qilin Sun, Yuming Fang   +5 more
wiley   +1 more source

Framework for the application of Explainable Artificial Intelligence techniques in the service of Democracy [PDF]

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceAs artificial intelligence is increasingly deployed in democracies around the ...
Encarnação, Marta Sofia Marques da
core  

Explainable Artificial Intelligence for Drug Discovery and Development: A Comprehensive Survey

IEEE Access
The field of drug discovery has experienced a remarkable transformation with the advent of artificial intelligence (AI) and machine learning (ML) technologies.
Roohallah Alizadehsani, Solomon Sunday Oyelere, Sadiq Hussain, Senthil Kumar Jagatheesaperumal, Rene Ripardo Calixto, Mohamed Rahouti, Mohamad Roshanzamir, Victor Hugo C. De Albuquerque   +7 more
doaj   +1 more source

A Bibliometric Analysis to Study the Evolution of Artificial Intelligence in Business Ethics

Business Ethics, the Environment &Responsibility, EarlyView.
ABSTRACT The contemporary world is witnessing the pervasive diffusion of artificial intelligence (AI) across diverse societal domains. Concurrently, the implementation of these technologies in numerous management areas raises novel and critical ethical considerations.
Mario Tani, Valerio Muto, Gianpaolo Basile, Giulia Nevi   +3 more
wiley   +1 more source