Latest AI and machine learning research in surveys for healthcare professionals.
Artificial intelligence (AI) is increasingly embedded in clinical environments, raising questions of trust, fairness, empathy, and governance. The ethical terrain surrounding AI in medicine remains unstable despite its rapid adoption. We introduce the "Seven Deadly Sins of AI in Medicine", a conceptual framework of recurring systemic failure modes: (i) Blind Trust, (ii) Overregulation, (iii) Dehum...
Deep learning models, particularly convolutional neural networks, have demonstrated remarkable performance in regression and classification tasks involving spectroscopic data. However, their black-box nature is considered a major drawback limiting the applicability of the methods. This paper provides a comprehensive tutorial on gradient-based methods that address this problem by providing informat...
INTRODUCTION: Student evaluations influence faculty promotion but may reflect implicit bias. We assessed whether surgeon gender, race, age, and experi...
BACKGROUND: The Pediatric Assessment Triangle (PAT) is a rapid visual assessment framework designed to support early identification of critically ill ...
Accurate neoantigen prediction is central to the design of personalized cancer immunotherapy. The immune recognition of neoantigens is a multi-step pr...
RATIONALE AND OBJECTIVES: Nasopharyngeal carcinoma (NPC) is characterized by a distinctive virologic and immunologic profile, in which Epstein-Barr vi...
OBJECTIVES: Head and body movements influence real-world hearing outcomes, yet they are often overlooked in clinical evaluations of hearing aids. This...
Sleep disturbances are highly prevalent and clinically significant non-motor features of Parkinson's disease (PD). Although in-laboratory polysomnogra...
PURPOSE: The purpose of this systematic review was to compare the inter- and intra-observer reliability of Kellgren-Lawrence (KL) grading versus minim...
The emergence of Large Vision-Language Models (LVLMs) marks significant strides towards achieving general artificial intelligence. However, these adva...
BACKGROUND: Digital health tools integrating electronic patient-reported outcome and experience measures (ePROMs/ePREMs) enable longitudinal monitorin...
BACKGROUND: As the demand for innovative older adult care grows alongside a shortage of care workers, personalization is key to optimizing services an...
PURPOSE: This study aimed to assess healthcare professionals' acceptance of artificial intelligence technologies within the framework of the Technolog...
The promotion and application of pulmonary function tests (PFTs) in China have achieved preliminary success;however, numerous deficiencies persist in ...
OBJECTIVE: Voice-based biomarkers have been proposed as objective tools for anxiety assessment, yet existing research relies on small, demographically...
UNLABELLED: Despite advances in pharmacotherapy, many patients with inflammatory arthritis (IA) experience residual pain even in remission. Digital he...
PURPOSE: This study aimed to quantify the prevalence and use cases of large language models (LLMs) among dental students, estimate perceived usefulnes...
BACKGROUND: Ultrasound is the standard imaging test for infant developmental dysplasia of the hip (DDH) but is highly operator-dependent, leading to v...
This research evaluates the factors influencing the behavioural intention (BI) to adopt large language models (LLMs) among dental students in educatio...
OBJECTIVES: Leveraging routine electronic health records (EHR) for dementia detection is a growing field, but quality and clinical utility of existing...