AI Medical Compendium Journal:
Digital health

Showing 11 to 20 of 22 articles

We asked Chat GPT to describe brain fog in chronic pain: What did we learn?

Digital health
Chat GPT is a modern artificial intelligence program: its recent introduction has created controversy in the academic world. This commentary discusses the utility of Chat GPT to explore healthcare issues such as chronic pain and associated conditions...

Feasibility and acceptability of ChatGPT generated radiology report summaries for cancer patients.

Digital health
OBJECTIVE: Patients now have direct access to their radiology reports, which can include complex terminology and be difficult to understand. We assessed ChatGPT's ability to generate summarized MRI reports for patients with prostate cancer and evalua...

Critical analysis of the AI impact on the patient-physician relationship: A multi-stakeholder qualitative study.

Digital health
OBJECTIVE: This qualitative study aims to present the aspirations, expectations and critical analysis of the potential for artificial intelligence (AI) to transform patient-physician relationship, according to multi-stakeholder insight.

How do nurses work in chronic management in the age of artificial intelligence? development and future prospects.

Digital health
AI is undeniably revolutionizing medical research and patient care across diverse fields. Chronic disease nursing care, a pivotal aspect of clinical management, has significantly reaped the benefits of AI across numerous dimensions. Understanding the...

The preliminary efficacy of virtual agent-assisted intelligent rehabilitation treatment (Echo app v2.0) in patients with alcohol use disorders: Study protocol for a randomized controlled trial.

Digital health
BACKGROUND: Alcohol use disorder (AUD) is one of the most common substance use disorders. People with AUD are in great need of highly accessible and comprehensive management, involving medicine, exercise, and psychotherapy. However, due to limited re...

Long-term effects of deep-learning digital therapeutics on pain, movement control, and preliminary cost-effectiveness in low back pain: A randomized controlled trial.

Digital health
OBJECTIVE: The present study aimed to compare the effects of a deep learning-based digital application with digital application physical therapy (DPT) and those of conventional physical therapy (CPT) on back pain intensity, limited functional ability...

Comparison of artificial intelligence-assisted informed consent obtained before coronary angiography with the conventional method: Medical competence and ethical assessment.

Digital health
OBJECTIVE: At the time of informed consent (IC) for coronary angiography (CAG), patients' knowledge of the process is inadequate. Time constraints and a lack of personalization of consent are the primary causes of inadequate information. This procedu...

Artificial intelligence (AI) in restorative dentistry: Performance of AI models designed for detection of interproximal carious lesions on primary and permanent dentition.

Digital health
OBJECTIVE: The objective of this study was to evaluate the effectiveness of deep learning methods in detecting dental caries from radiographic images.

The ensemble artificial intelligence (AI) method: Detection of hip fractures in AP pelvis plain radiographs by majority voting using a multi-center dataset.

Digital health
INTRODUCTION: This article was undertaken to explore the potential of AI in enhancing the diagnostic accuracy and efficiency in identifying hip fractures using X-ray radiographs. In the study, we trained three distinct deep learning models, and we ut...

Evaluating online health information quality using machine learning and deep learning: A systematic literature review.

Digital health
BACKGROUND: Due to the large volume of online health information, while quality remains dubious, understanding the usage of artificial intelligence to evaluate health information and surpass human-level performance is crucial. However, the existing s...