AIMC Topic: Patient Participation
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Applying the UTAUT2 framework to patients' attitudes toward healthcare task shifting with artificial intelligence.
BMC health services research
Apr 11, 2024
BACKGROUND: Increasing patient loads, healthcare inflation and ageing population have put pressure on the healthcare system. Artificial intelligence and machine learning innovations can aid in task shifting to help healthcare systems remain efficient...
Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials.
Cancer imaging : the official publication of the International Cancer Imaging Society
Apr 5, 2024
BACKGROUND: Ductal Carcinoma In Situ (DCIS) can progress to invasive breast cancer, but most DCIS lesions never will. Therefore, four clinical trials (COMET, LORIS, LORETTA, AND LORD) test whether active surveillance for women with low-risk Ductal ca...
Monitoring Active Patient Participation During Robotic Rehabilitation: Comparison Between a Robot-Based Metric and an EMG-Based Metric.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 26, 2023
While rehabilitation robots present a much-needed solution to improving early mobilization therapy in demanding clinical settings, they also present new challenges and opportunities in patient monitoring. Aside from the fundamental challenge of quant...
Revolutionizing healthcare: the role of artificial intelligence in clinical practice.
BMC medical education
Sep 22, 2023
INTRODUCTION: Healthcare systems are complex and challenging for all stakeholders, but artificial intelligence (AI) has transformed various fields, including healthcare, with the potential to improve patient care and quality of life. Rapid AI advance...
Artificial Intelligence Chatbots in Allergy and Immunology Practice: Where Have We Been and Where Are We Going?
The journal of allergy and clinical immunology. In practice
Jun 8, 2023
Artificial intelligence (AI) is rapidly becoming a valuable tool in healthcare, providing clinicians with a new AI lens perspective for patient care, diagnosis, and treatment. This article explores the potential applications, benefits, and challenges...
Potential Use Cases for ChatGPT in Radiology Reporting.
AJR. American journal of roentgenology
Apr 19, 2023
Large language models (LLMs) such as ChatGPT are advanced artificial intelligence models that are designed to process and understand human language. LLMs have the potential to improve radiology reporting and patient engagement by automating generatio...
Evaluating the safety and patient impacts of an artificial intelligence command centre in acute hospital care: a mixed-methods protocol.
BMJ open
Mar 1, 2022
INTRODUCTION: This paper presents a mixed-methods study protocol that will be used to evaluate a recent implementation of a real-time, centralised hospital command centre in the UK. The command centre represents a complex intervention within a comple...
Nothing about us without us: involving patient collaborators for machine learning applications in rheumatology.
Annals of the rheumatic diseases
Jul 5, 2021
Novel machine learning methods open the door to advances in rheumatology through application to complex, high-dimensional data, otherwise difficult to analyse. Results from such efforts could provide better classification of disease, decision support...
Use and Control of Artificial Intelligence in Patients Across the Medical Workflow: Single-Center Questionnaire Study of Patient Perspectives.
Journal of medical Internet research
Feb 17, 2021
BACKGROUND: Artificial intelligence (AI) is gaining increasing importance in many medical specialties, yet data on patients' opinions on the use of AI in medicine are scarce.
From Patient Engagement to Precision Oncology: Leveraging Informatics to Advance Cancer Care.
Yearbook of medical informatics
Aug 21, 2020
OBJECTIVES: Conduct a survey of the literature for advancements in cancer informatics over the last three years in three specific areas where there has been unprecedented growth: 1) digital health; 2) machine learning; and 3) precision oncology. We a...
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