AIMC Journal:
Studies in health technology and informatics

Showing 271 to 280 of 1224 articles

Initial Investigations into Physician Acceptance of Medical AI: Examining Trust, Resistance, Perceived Job Insecurity, and Usage Intentions.

Studies in health technology and informatics
This study evaluated physicians' attitudes towards medical AI across three Taiwanese hospitals, focusing on constructs of trust, resistance, job insecurity, and adoption willingness, with a survey based on the Dual-factor Model yielding 282 responses...

Evaluating ChatGPT 4.0's User Satisfaction Among Doctors Across Different Medical Departments.

Studies in health technology and informatics
In an era increasingly focused on integrating Artificial Intelligence (AI) into healthcare, the utility and user satisfaction of AI applications like ChatGPT have become pivotal research areas. This study, conducted in Greece, engaged 193 doctors fro...

Designing a Social Snus Cessation Mobile Application with an Integrated AI Function.

Studies in health technology and informatics
The application of artificial intelligence (AI) in healthcare is expected to be increased in the coming years. There has been little attention paid on exploring how social aspects and AI can be integrated into mobile applications to support the peopl...

Unveiling the Potential of ChatGPT and YOLOv7 for Evaluating Children's Emotions Using Their Artistic Expressions.

Studies in health technology and informatics
Recent advancements in large language models (LLMs) have sparked considerable interest in their potential applications across various healthcare domains. One promising prospect is leveraging these generative models to accurately predict children's em...

Towards Autonomous Living Meta-Analyses: A Framework for Automation of Systematic Review and Meta-Analyses.

Studies in health technology and informatics
Systematic review and meta-analysis constitute a staple of evidence-based medicine, an obligatory step in developing the guideline and recommendation document. It is a formalized process aiming at extracting and summarizing knowledge from the publish...

Using Natural Language Processing on Expert Panel Discussions to Gain Insights for Recruitment, Retention and Intervention Adherence for Online Social Support Interventions on a Stage II-III Clinical Trial Among Hispanic and African American Dementia Caregivers.

Studies in health technology and informatics
We applied natural language processing (NLP) to a corpus extracted from 4 hours of expert panel discussion transcripts to determine the sustainability of a Stage II-III clinical trial of online social support interventions for Hispanic and African Am...

Integrating Chatbot Functionality in a Patient Summary Based Healthcare System.

Studies in health technology and informatics
The integration of chatbots in healthcare has gained attention due to their potential to enhance patient engagement and satisfaction. This paper presents a healthcare chatbot providing comprehensive access to patient summaries, aligned with the Europ...

Machine Learning with Clinical and Intraoperative Biosignal Data for Predicting Cardiac Surgery-Associated Acute Kidney Injury.

Studies in health technology and informatics
Early identification of patients at high risk of cardiac surgery-associated acute kidney injury (CSA-AKI) is crucial for its prevention. We aimed to leverage perioperative clinical and intraoperative biosignal data to develop machine learning models ...

Comparing NER Approaches on French Clinical Text, with Easy-to-Reuse Pipelines.

Studies in health technology and informatics
The task of Named Entity Recognition (NER) is central for leveraging the content of clinical texts in observational studies. Indeed, texts contain a large part of the information available in Electronic Health Records (EHRs). However, clinical texts ...

Unsupervised Extraction of Body-Text from Clinical PDF Documents.

Studies in health technology and informatics
Automatic extraction of body-text within clinical PDF documents is necessary to enhance downstream NLP tasks but remains a challenge. This study presents an unsupervised algorithm designed to extract body-text leveraging large volume of data. Using D...