explainable ai

Building Ethical AI Competencies in STEM Education

The importance of AI ethics in STEM education is to train future technologists on how to create socially useful and responsible AI systems. It focuses on the incorporation of governance systems, transparency, and responsible innovation into the school curricula. Governance guarantees responsible behavior and ethical co...

Loss-Aware Residual Learning for Imbalanced Multi-Class Diabetic Retinopathy Diagnosis

A novel deep learning model based on Residual Networks (ResNet) is proposed to address the multi class classification of DR, with a focus on mitigating class imbalance, highlighting the model's effectiveness in addressing class imbalance and its potential for early DR diagnosis, thereby enhancing clinical decision supp...

Marketing Analytics for Gastrointestinal Cancer Prevention and Early Detection: Emerging Trends, Analytical Frameworks and Research Directions

Gastrointestinal (GI) cancers, such as colorectal, gastric, liver, pancreatic, and oesophageal cancers, continue to represent a serious public health concern because of their high prevalence and mortality and frequent delayed diagnosis. The evolution of marketing analytics offers new opportunities to address existing b...

Clinically Actionable Explainable Artificial Intelligence: A Risk-Aware Framework for Translating Model Explanations into Medical Decisions

Explainable Artificial Intelligence is now widely used in the healthcare sector in order to increase transparency in AI prediction models which can be used for diagnosis, risk prediction, and decision-making. Although currently used explainability techniques can justify predictions, in most cases they do not effectivel...

Artificial Intelligence Derived from Ancient Indian Practices in Chemistry

This chapter explores the intersection between the Ancient Indian Practices (AIP) and Artificial Intelligence (AI), highlighting the relevance of the traditional Indian Knowledge System (IKS) to the advancement of chemical sciences. The vast data of the Indian Knowledge System are available in the form of textual mater...

Ethical AI in Practice

The swift incorporation of artificial intelligence (AI) into science, technology, engineering, and mathematics (STEM) education has generated revolutionary prospects for customized learning, intelligent tutoring, predictive analytics, and automated evaluation. But with these benefits come important ethical issues that...

Investigating AI/ML Models that Learn the Preferences and Constraints of Human Decision-Makers to Develop Interactive or Tools that Suggest Optimized Solutions While Allowing for Human Override and Incorporating Expert Judgment

The growing adoption of Artificial Intelligence and Machine Learning (AI/ML) systems in very complicated and sensitive decision-making areas have had a big impact on the issues of transparency, trust, and ethical accountability. The optimization-based AI systems were mainly focusing on maximizing the computational effi...

From Algorithms to Clinics: Evaluating AI’s Role in Pediatric Autism Diagnosis

From High-Level Ethics to Actionable Measures

The active evolution of technology has led to new changes, and one of the trends that has become topical and actively discussed within the academic community and society in general is Artificial Intelligence (AI). Nevertheless, it has turned out that the data on which AI systems are built is not always neutral. This ha...

Socially (dis)connected consumer trust in AI technologies: a systematic review and research agenda

Purpose Loneliness, as a mental health epidemic alongside the artificial intelligence (AI) improvements, has received attention in the literature. Motivated by the need to belong, lonely consumers experience psychological states that influence their trust in AI, resulting in inconsistent findings in this emerging resea...

Effects of Human-AI Voice Interaction in Sports Commentary on Perceived Credibility, Emotional Response, and Cognitive Recall

This study examines how commentary source (human vs. artificial intelligence [AI]), commentator gender, and accent shape perceived credibility, affective responses, and cognitive recall in sports broadcasting. A 2 (source) × 2 (commentator gender) × 2 (accent) between-subjects experiment (N = 867) showed that human-voi...

Measles and Rubella Surveillance in the Digital Era

The integration of digital technologies has profoundly transformed the surveillance of infectious diseases over recent decades. The emergence of approaches grounded in digital health, genomic surveillance, health information systems, and data analytics opens new perspectives for measles and rubella surveillance. The pr...