PhilArchive
open access
Trust in Medical AI: The Case of mHealth Diabetes Apps
Over the past few years, mobile health applications (mHealth apps) have gained popularity regarding the management of chronic conditions, such as diabetes, as they are considered to enhance follow‐up and treatment. Indeed, these applications are powerful tools that support individualised pharmaceutical and non‐pharmaceutical care by remotely monitoring the patient's health status in real‐time. Nevertheless, concerns have been raised regarding trust and trustworthiness towards their use, in particular, when they are powered by Artificial Intelligence (AI). Trust in AI is a multifaceted notion that encompasses aspects such as reliance, risk, as well as ethical principles (e.g., respect for human autonomy and prevention of harm). In this paper, we provide an analysis of trust and trustworthiness in AI‐powered mHealth apps for diabetes through the lens of philosophy and risk analysis to promote the patient's well‐being.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Patients With Pancreatic Tumor: Use of an App to Monitor Progress in a Simple and Intuitive Way by Periodically Completing Targeted Questionnaires and Providing Educational and Informational Content (PancreasPlus).#1031793
- Increasing Preparedness Through a Website#895715
- The “inconvenient truth” about AI in healthcare#477121
- Testing the Utilization of a Mobile Health App for Patients Undergoing Cystectomy Surgery for Bladder Cancer#916254
- Patients’ Perceptions Toward Human–Artificial Intelligence Interaction in Health Care: Experimental Study#964517
Record · ID 108187
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive