Background: Artificial intelligence (AI) has potential to improve self-management of several chronic conditions. However, the perspective of patients and healthcare professionals regarding AI-enabled health management programs, which are key to successful implementation, remains poorly understood.
Purpose: To explore the opinions of people with a history of myocardial infarction (PHMI) and health professionals on the use of AI for secondary prevention of MI.
Procedure: Three rounds of focus groups were conducted via videoconferencing with 38 participants: 22 PHMI and 16 health professionals.
Findings: We identified 21 concepts stemming from participants' views, which we classified into five categories: Trust; Expected Functions; Adoption; Concerns; and Perceived Benefits. Trust covered the credibility of information and safety to believe health advice. Expected Functions covered tailored feedback and personalised advice. Adoption included usability features and overall interest in AI. Concerns originated from previous negative experience with AI. Perceived Benefits included the usefulness of AI to provide advice when regular contact with healthcare services is not feasible. Health professionals were more optimistic than PHMI about the usefulness of AI for improving health behaviour.
Conclusions: Altogether, our findings provide key insights from end-users to improve the likelihood of successful implementation and adoption of AI-enabled systems in the context of MI, as an exemplar of broader applications in chronic disease management.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.ijmedinf.2023.105041 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Small Molecular Oligopeptides Adorned with Tryptophan Residues as Potent Antitumor Agents: Design, Synthesis, Bioactivity Assay, Computational Prediction, and Experimental Validation.
J Chem Inf Model
January 2025
Key Laboratory for Photonic and Electronic Bandgap Materials, Ministry of Education, College of Chemistry and Chemical Engineering, Harbin Normal University, Harbin 150025, China.
Tryptophan participates in important life activities and is involved in various metabolic processes. The indole and aromatic binuclear ring structure in tryptophan can engage in diverse interactions, including π-π, π-alkyl, hydrogen bonding, cation-π, and CH-π interactions with other side chains and protein targets. These interactions offer extensive opportunities for drug development.
View Article and Find Full Text PDFNovel Strategies for the Treatment of Lung Cancer: An In-depth Analysis of the Use of Immunotherapy, Precision Medicine, and Artificial Intelligence to Improve Prognoses.
Curr Med Chem
January 2025
Shree S K Patel College of Pharmaceutical Education and Research, Ganpat University, Mahesana, Gujarat, 384012, India.
Therapeutic hurdles persist in the fight against lung cancer, although it is a leading cause of cancer-related deaths worldwide. Results are still not up to par, even with the best efforts of conventional medicine, thus new avenues of investigation are required. Examining how immunotherapy, precision medicine, and AI are being used to manage lung cancer, this review shows how these tools can change the game for patients and increase their chances of survival.
View Article and Find Full Text PDFArtificial intelligence-powered solutions for automated aortic diameter measurement in computed tomography: a narrative review.
Ann Transl Med
December 2024
Division of Cardiothoracic Surgery, Department of Surgery, The Chinese University of Hong Kong, Hong Kong, China.
Background And Objective: Patients with thoracic aortic aneurysm and dissection (TAAD) are often asymptomatic but present acutely with life threatening complications that necessitate emergency intervention. Aortic diameter measurement using computed tomography (CT) is considered the gold standard for diagnosis, surgical planning, and monitoring. However, manual measurement can create challenges in clinical workflows due to its time-consuming, labour-intensive nature and susceptibility to human error.
View Article and Find Full Text PDFArtificial intelligence in clinical settings: a systematic review of its role in language translation and interpretation.
Ann Transl Med
December 2024
Division of Advanced Gastrointestinal and Bariatric Surgery, Mayo Clinic, Jacksonville, FL, USA.
Background: Addressing language barriers through accurate interpretation is crucial for providing quality care and establishing trust. While the ability of artificial intelligence (AI) to translate medical documentation has been studied, its role for patient-provider communication is less explored. This review evaluates AI's effectiveness in clinical translation by assessing accuracy, usability, satisfaction, and feedback on its use.
View Article and Find Full Text PDFDiabetes mellitus and glymphatic dysfunction: Roles for oxidative stress, mitochondria, circadian rhythm, artificial intelligence, and imaging.
World J Diabetes
January 2025
National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20810, United States.
Diabetes mellitus (DM) is a debilitating disorder that impacts all systems of the body and has been increasing in prevalence throughout the globe. DM represents a significant clinical challenge to care for individuals and prevent the onset of chronic disability and ultimately death. Underlying cellular mechanisms for the onset and development of DM are multi-factorial in origin and involve pathways associated with the production of reactive oxygen species and the generation of oxidative stress as well as the dysfunction of mitochondrial cellular organelles, programmed cell death, and circadian rhythm impairments.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!