Background And Objective: Data on interaction of patients with artificial intelligence (AI) are limited, primarily derived from small-scale studies, cross-sectional surveys, and qualitative reviews. Most patients have not yet encountered AI in their clinical experience. This study explored patients' confidence in AI, specifically large language models, after a direct interaction with a chatbot in a clinical setting. Through hands-on experience, the study sought to reduce potential biases due to an anticipated lack of AI experience in a real-world urological patient sample.
Methods: A total of 300 patients scheduled for counseling were enrolled from February to July 2024. Participants voluntarily conversed about their medical questions with a GPT-4 powered chatbot, followed by a survey assessing their confidence in clinical capabilities of AI compared with their counseling urologists. Clinical capabilities included history taking, diagnostics, treatment recommendation, anxiety reduction, and time allocation.
Key Findings And Limitations: Of the 292 patients who completed the study, AI was significantly preferred to physicians for consultation time allocation ( < 0.001). However, urologists were overwhelmingly favored for all other capabilities, especially treatment recommendations and anxiety reduction. Notably, age did not influence patients' confidence in AI. Limitations include a potential social desirability bias.
Conclusions And Clinical Implications: Our study demonstrates that urological patients prefer AI as a powerful complement to-rather than a replacement for-human expertise in clinical care. Patients appreciated the additional consultation time provided by AI. Interestingly, age was not associated with confidence in AI, suggesting that large language models are user-friendly tools for patients of all age groups.
Patient Summary: In this report, we explored how patients feel about using an artificial intelligence (AI)-powered chatbot in a medical setting. Patients interacted with the AI for medical questions and compared its skills with those of doctors through a survey. They appreciated the AI for providing more time during consultations but preferred doctors for other tasks, for example, diagnostics, recommendation of treatments, and reduction of anxieties.
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http://dx.doi.org/10.1016/j.euros.2024.10.009 | DOI Listing |
Sci Rep
December 2024
Department of Pharmaceutics, College of Pharmacy, University of Ha'il, Ha'il, 81442, Saudi Arabia.
This research article presents a thorough and all-encompassing examination of predictive models utilized in the estimation of viscosity for ionic liquid solutions. The study focuses on crucial input parameters, namely the type of cation, the type of anion, the temperature (measured in Kelvin), and the concentration of the ionic liquid (expressed in mol%). This study assesses three influential machine learning algorithms that are based on the Decision Tree methodology.
View Article and Find Full Text PDFSmall
December 2024
State Key Laboratory of Oral Diseases, School of Chemical Engineering, National Center for Stomatology & National Clinical Research Center for Oral Diseases, Sichuan University, Chengdu, 610041, China.
Intractable implant-associated infections (IAIs) are the primary cause of prosthetic implant failure, particularly in the context of diabetes mellitus. There is an urgent need to design and construct versatile engineered implants integrated with cascade amplification therapeutic modality to significantly improve the treatment of diabetic IAIs. To address this issue, a multi-functional MXene/AgPO@glucose oxidase bio-heterojunction enzyme (M/A@GOx bio-HJzyme) coating is developed, which is decorated with an inert sulfonated polyetheretherketone implant (SP-M/A@G) via hydrothermal treatment and layered deposition.
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December 2024
Department of Dermatology, Veterans Health Administration, San Antonio, Texas, USA.
Objectives: Glomangiomas are benign vascular malformations that exist within the spectrum of glomuvenous malformations which consist of varying amounts of glomus cells, vascular spaces, and smooth muscle. Glomangiomas are often treated due to associated pain, particularly when located on pressure areas such as the back or extensor surfaces, which can cause difficulty with certain activities and occupational functions. Histologically glomangiomas consist of prominent dilated vascular spaces lined by glomus cells typically situated in the deep-dermis to subcutaneous fat which limits treatment to modalities capable of reaching the depth of the tumor including excision, sclerotherapy, and laser therapy.
View Article and Find Full Text PDFIJID Reg
March 2025
Programme for Research in Epidemic Preparedness and Response (PREPARE), Ministry of Health, Singapore.
The COVID-19 pandemic highlighted the critical need for well-established clinical research networks capable of rapid response during infectious disease outbreaks. In Southeast Asia, the absence of active research networks at the onset of the COVID-19 contributed to gaps in regional preparedness. This manuscript discusses the challenges and opportunities identified during a regional workshop held in Singapore (February 26 to March 1, 2024), which brought together 130 stakeholders from across the region.
View Article and Find Full Text PDFFront Psychol
December 2024
Department of Psychology, University of Turin, Turin, Italy.
Occupational and/or environmental exposure to asbestos can lead to clinical manifestation of a variety of diseases, including malignant mesothelioma (MM), a rare cancer with a particularly high incidence rate in areas with a long history of asbestos processing. This paper aims to describe brief psychoanalytic groups (BPGs), which is an intervention model aimed at MM patients and their families in the early stages of the disease, shortly after diagnosis. The BPG model comprises 12 weekly sessions of 1 h each, co-led by two psychoanalytically oriented psychotherapists who are trained in working with cancer patients and their families and in the specifics of the BPG setting.
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