AIMC Topic: User-Centered Design

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Assessing the Involvement of Users During Development of Lower Limb Wearable Robotic Exoskeletons: A Survey Study.

Human factors
OBJECTIVE: To explore user-centered design methods currently implemented during development of lower limb wearable robots and how they are utilized during different stages of product development.

User-Centered Methods in Explainable AI Development for Hospital Clinical Decision Support: A Scoping Review.

Studies in health technology and informatics
Explainable Artificial Intelligence (XAI) offers promising advancements in enhancing transparency and usability of AI-based Clinical Decision Support Systems (CDSS) in healthcare settings. These tools aim to improve clinical outcomes by assisting wit...

Universally Designed Augmented Reality as Interface for Artificial Intelligence Assisted Decision-Making in Everyday Life Scenarios.

Studies in health technology and informatics
This paper presents a conceptual prototype that integrates Artificial Intelligence (AI) and Augmented Reality (AR) with the principles of Universal Design (UD) to enhance decision-making in everyday scenarios for a diverse user base, eliminating the ...

User-Centered Development of Explanation User Interfaces for AI-Based CDSS: Lessons Learned from Early Phases.

Studies in health technology and informatics
This paper reports lessons learned during the early phases of the user-centered design process for an explanation user interface for an AI-based clinical decision support system for the intensive care unit. This paper focuses on identifying and verif...

Exploring the Intersection of AI and Inclusive Design for People with Disabilities.

Studies in health technology and informatics
This scoping review examines current research on AI for inclusive design for people with disabilities. We identified both advantages and challenges of AI-based solutions and suggested future research directions. Our search of four online databases fo...

User-centred design for machine learning in health care: a case study from care management.

BMJ health & care informatics
OBJECTIVES: Few machine learning (ML) models are successfully deployed in clinical practice. One of the common pitfalls across the field is inappropriate problem formulation: designing ML to fit the data rather than to address a real-world clinical p...