Results 21 to 30 of about 78,288 (166)

Explainable Artificial Intelligence in the Early Diagnosis of Gastrointestinal Disease

Diagnostics, 2022
This study reviews the recent progress of explainable artificial intelligence for the early diagnosis of gastrointestinal disease (GID). The source of data was eight original studies in PubMed.
Kwang-Sig Lee, Eun Sun Kim
doaj   +1 more source

A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems [PDF]

, 2019
We propose a set of compositional design patterns to describe a large variety of systems that combine statistical techniques from machine learning with symbolic techniques from knowledge representation.
Teije, Annette ten, van Harmelen, Frank
core   +2 more sources

Explainable Artificial Intelligence (XAI) in Insurance

Risks, 2022
Explainable Artificial Intelligence (XAI) models allow for a more transparent and understandable relationship between humans and machines. The insurance industry represents a fundamental opportunity to demonstrate the potential of XAI, with the industry ...
Emer Owens, Barry Sheehan, Martin Mullins, Martin Cunneen, Juliane Ressel, German Castignani   +5 more
doaj   +1 more source

Explainable Artificial Intelligence for Kids [PDF]

Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (EUSFLAT 2019), 2019
Artificial Intelligence (AI) is part of our everyday life and has become one of the most outstanding and strategic technologies of the 21st century. Explainable AI (XAI in short) is expected to endow AI systems with explanation ability when interacting with humans.
openaire   +1 more source

Research Progress of Interpretable Artificial Intelligence [PDF]

Jisuanji gongcheng
Artificial intelligence has made remarkable progress across many fields, encouraging countries to attach great importance to its research and development.
LIAO Yong, HAN Xiaojin, LIU Jinlin, WANG Hao
doaj   +1 more source

Context-Aware Negative Sampling for Sequential Recommendation

IEEE Access
Recommender systems have become essential in large-scale e-commerce and content platforms. While user preferences are crucial in generating recommendations, the context in which recommendations are made—such as time, location, and occasion— ...
Jinseok Seol, Jaesik Choi
doaj   +1 more source

Robot Mindreading and the Problem of Trust [PDF]

, 2020
This paper raises three questions regarding the attribution of beliefs, desires, and intentions to robots. The first one is whether humans in fact engage in robot mindreading. If they do, this raises a second question: does robot mindreading foster trust
Páez, Andrés
core   +1 more source

Instantiating the onEEGwaveLAD Framework for Real-Time Muscle Artefact Identification and Mitigation in EEG Signals

Sensors
While electroencephalography is extremely useful for studying brain activity, EEG data is always contaminated by a wide range of artefacts. Many techniques exist to identify and remove such artefacts, primarily offline, with and without human supervision
Luca Longo, Richard Reilly
doaj   +1 more source

The Grammar of Interactive Explanatory Model Analysis

, 2021
The growing need for in-depth analysis of predictive models leads to a series of new methods for explaining their local and global properties. Which of these methods is the best? It turns out that this is an ill-posed question.
Baniecki, Hubert, Biecek, Przemyslaw
core  

On the Need of an Explainable Artificial Intelligence [PDF]

, 2019
This plenary talk will explore a fascinating nex research field: the Explainable Artificial Intelligence (or XAI), whose goal if the building of explanatory models, to try and overcome the shortcomings of pure statistical learning by providing justifications, understandable by a human, for decisions or predictions made by them.
openaire   +3 more sources