Results 161 to 170 of about 55,142 (282)

Explainable Artificial Intelligence in Healthcare: Current Landscape, Challenges, and Future Directions. [PDF]

Health Sci Rep
Shiddik MAB.
europepmc   +1 more source

AI Alignment Versus AI Ethical Treatment: 10 Challenges

Analytic Philosophy, EarlyView.
ABSTRACT A morally acceptable course of AI development should avoid two dangers: creating unaligned AI systems that pose a threat to humanity and mistreating AI systems that merit moral consideration in their own right. This paper argues these two dangers interact and that if we create AI systems that merit moral consideration, simultaneously avoiding ...
Adam Bradley, Bradford Saad
wiley   +1 more source

Explainable AI in healthcare: a systematic review of XAI use cases in imaging, diagnostics, and rehabilitation. [PDF]

Front Artif Intell
Aravindkumar A, Ramadoss M, Fakhruddin Ahmed SA, Sampath V, Lakshminarayanan K.   +4 more
europepmc   +1 more source

Personalized Model‐Driven Interventions for Decisions From Experience

Topics in Cognitive Science, EarlyView.
Abstract Cognitive models that represent individuals provide many benefits for understanding the full range of human behavior. One way in which individual differences emerge is through differences in knowledge. In dynamic situations, where decisions are made from experience, models built upon a theory of experiential choice (instance‐based learning ...
Edward A. Cranford, Christian Lebiere, Cleotilde Gonzalez, Palvi Aggarwal, Sterling Somers, Konstantinos Mitsopoulos, Milind Tambe   +6 more
wiley   +1 more source

Do Humans and GAI See Eye to Eye? Implications of LLM Scoring Volatility in Supplier Evaluations

Journal of Business Logistics, Volume 47, Issue 3, July 2026.
ABSTRACT This study compares Generative Artificial Intelligence (GAI) to human procurement professionals on supplier evaluation tasks. Using Structural Topic Modeling (STM) on 123 government supplier bids from 31 projects solicited by the State of Ohio between January 2023 and December 2024, we compare evaluations from three reasoning models (o3, Grok ...
Finnegan A. McKinley, Anne E. Dohmen, Vincent E. Castillo   +2 more
wiley   +1 more source

Light-XAI: a CADx for explainable cervical cancer detection via attention-based lightweight convolutional neural networks and layer-wise feature fusion. [PDF]

BioData Min
Attallah O.
europepmc   +1 more source

On Using the Shapley Value for Anomaly Localization: A Statistical Investigation

Applied AI Letters, Volume 7, Issue 2, June 2026.
ABSTRACT Recent publications have suggested using the Shapley value for anomaly localization for sensor data systems. We use a reasonable statistical model for the classifiers required to compute the Shapley value to provide repeatable and rigorous analysis in the anomaly localization application.
Rick S. Blum, Xubin Fang, Franziska Freytag   +2 more
wiley   +1 more source

An intelligent healthcare framework for hepatocellular carcinoma diagnosis based on aggregated learners from biomedical data utilising explainable artificial intelligence. [PDF]

Sci Rep
Alqaralleh BAY, Alksasbeh MZ, Kulakli A, Zreikat AI.   +3 more
europepmc   +1 more source

User‐Based Evaluation of Explainability Techniques for Misogyny Detection in Code‐Mixed Hindi–English

Applied AI Letters, Volume 7, Issue 2, June 2026.
In this work, we have performed human‐based evaluation of three post hoc explainability techniques, Local Interpretable Model Agnostic Explanations (LIME), Shapely Additive Explanations (SHAP), and integrated Gradients (IG) for a multilingual Bidirectional Encoder Representations from Transformers (mBERT) based binary and multi‐label misogyny ...
Sargam Yadav, Abhishek Kaushik, Kevin McDaid   +2 more
wiley   +1 more source

A comprehensive review of explainable artificial intelligence in healthcare methods, evaluation, and clinical integration. [PDF]

iScience
Zhang K, Wang D, Lin F, Xie J, Zhou W.
europepmc   +1 more source