AIMC Topic: Artificial Intelligence

Clear Filters Showing 20661 to 20670 of 26332 articles

Clustering Voice of the Customer Insights: Identifying Key Needs for AI-Based Early Warning System.

Studies in health technology and informatics
In this study, we analyzed voice of customer (VOC) data for an AI-based early warning system from healthcare providers using the BERTopic framework for effective topic modeling. A preprocessing pipeline was implemented, incorporating techniques such ...

Intelligent System for Automated Spheroid Segmentation Using Machine Learning.

Studies in health technology and informatics
Image segmentation is a crucial task of medical image processing, including the analysis of multicellular tumour spheroids (MTSs), a common in vitro model used in cancer research for drug screening. Accurate segmentation of MTSs images allows the ext...

How Useful Is Synthetic Data in Developing Predictive Models for Health?

Studies in health technology and informatics
Synthetic data, generated using generative AI techniques, closely mimics the characteristics of real data while enhancing privacy for sensitive health data. This study evaluates synthetic tabular data based on fidelity and utility for predictive mode...

Exploring Differential Diagnosis-Based Explainable AI: A Case Study in Melanoma Detection.

Studies in health technology and informatics
Melanoma is a significant global health concern, with rising incidence rates and high mortality when diagnosed late. Artificial Intelligence (AI) models, especially models using deep learning techniques, have shown promising results in melanoma detec...

Examining Physicians' Intentions to Use AI: The Roles of Accountability, Necessity, and Usefulness.

Studies in health technology and informatics
This study explores the under-researched area of how perceived necessity and accountability influence physicians' intention to use AI in healthcare. Conducted across three general hospitals in Taiwan, the research analyzed 398 valid responses from ph...

Comparing a Top-Down and a Bottom-Up Approach for Implementing AI in Radiology Practice.

Studies in health technology and informatics
This paper examines how two health regions in Norway adopted different strategies for implementing commercial AI algorithms to outline. One region employs a top-down, research-driven approach, while the other takes a bottom-up, innovation-focused app...

From Healthcare Technology to Care Robot-Literate Practitioners.

Studies in health technology and informatics
Current forms of health technology literacies fail to fully address the multifaceted nature of care robot literacy (CRL). As an occupational asset for healthcare practitioners, CRL involves the ability to use and interact with mobile, artificially in...

Beyond Model Performance: Information Needs for an Algorithmovigilance Sociotechnical System.

Studies in health technology and informatics
Proactive and ongoing monitoring of AI systems, or algorithmovigilance, is essential for mitigating patient safety risks from AI in healthcare. In this study, we describe the information needs for an AI monitoring and operations system and provide de...

Participatory Design of an AI-Based CDSS for Delirium Prevention.

Studies in health technology and informatics
Delirium is a frequent and severe complication in inpatient care, leading to increased mortality and cognitive impairment. The KIDELIR project aims to develop a clinical decision support system (CDSS) based on artificial intelligence (AI) to predict ...

Co-Designing AI Interventions: A Participatory Approach Using System Mapping and Theory of Change Modelling.

Studies in health technology and informatics
In a workshop setting, Participatory Systems Mapping and Theory of Change modelling were employed for the purpose of analysing clinical workflows and assessing the integration of an AI-based prediction system. These methods aimed to visualise challen...