Trust and anxiety as primary drivers of digital health acceptance in multiple sclerosis: toward an extended disease-specific technology acceptance model [0.03%]
Felix Höpfl,Mira Brundiers
Felix Höpfl
Background: Digital health applications and AI-supported wearables may benefit people with Multiple Sclerosis (MS), yet fluctuating cognitive and physical symptoms could shape adoption in ways not fully captured by tradit...
Stijn Denissen,Jorne Laton,Matthias Grothe et al.
Stijn Denissen et al.
Background: Federated learning (FL) has the potential to boost deep learning in neuroimaging but is rarely deployed in real-world scenarios, where its true potential lies. We propose FLightcase, a new FL toolbox tailored ...
Jihane Ghorayeb,Rupa Kalahasthi,Niki Hosseini-Kamkar
Jihane Ghorayeb
Objective: The paper aims to systematically review the literature on the efficacy of virtual reality (VR) based therapies to treat mental health disorders in Randomized Control Trials (RCTs). ...
Through the looking glass: ethical considerations regarding LLM-induced hallucinations to medical questions [0.03%]
Zisis Kozlakidis,Tracy Wootton,Michaela Th Mayrhofer
Zisis Kozlakidis
Fatma Nur Cicin,Güney Çetin Gürkan
Fatma Nur Cicin
Objective: This study investigates the factors influencing physicians' acceptance and adoption of artificial intelligence (AI) technologies in clinical practice, integrating the Theory of Planned Behavior (TPB) and the Te...
How hospital accreditation requirements bridge enablers for AI readiness: interpretative analysis of intersections in framework standards [0.03%]
Ericles Andrei Bellei,Raquel Debon,Elísio Costa et al.
Ericles Andrei Bellei et al.
Correction: Adopting machine learning to predict breast cancer patients adherence with lifestyle recommendations and quality of life outcomes [0.03%]
Anna Crispo,Elisabetta Pagnano,Agnese Bonfigli et al.
Anna Crispo et al.
[This corrects the article DOI: 10.3389/fdgth.2025.1645233.]. Keywords: breast cancer; diet; health-related ...
Published Erratum
Frontiers in digital health. 2026 Mar 11:8:1804768. DOI:10.3389/fdgth.2026.1804768 2026
Peter Kosa,Amir Moghadam Ahmadi,Marie Kanu et al.
Peter Kosa et al.
Introduction: Detecting subtle cognitive decline in chronic central nervous system (CNS) disease is hampered by practice effects, motor confounds, and the lack of premorbid baselines. Smartphone testing offers frequent un...
From inferring preferences to enabling choice: potentials of digital tools to improve substitute decision-making [0.03%]
Florian Funer,Christin Hempeler
Florian Funer
Respect for patient autonomy is a foundational principle in healthcare ethics, which holds that patients can make their own treatment decisions. However, sometimes patients lack the capacity to do so and surrogates must decide on their beha...
Unlocking electronic health records: a hybrid graph RAG approach to safe clinical AI for patient QA [0.03%]
Samuel Thio,Matthew Lewis,Spiros Denaxas et al.
Samuel Thio et al.
Introduction: Electronic health record (EHR) systems present clinicians with vast repositories of clinical information, creating a significant cognitive burden where critical details are easily overlooked. While Large Lan...