Latest AI and machine learning research in patient safety / risk management for healthcare professionals.
PURPOSE: To evaluate the performance of a customized deep learning algorithm for automated segmentation of nonperfusion area (NPA) on ultra-widefield swept-source OCTA (UWF SS-OCTA) and its utility in diabetic retinopathy (DR) severity assessment. DESIGN: Cross-sectional study. SUBJECTS: A total of 180 eyes from 122 participants representing all grades of DR severity. METHODS: We developed a convo...
Generative Artificial Intelligence (GenAI) tools are increasingly integrated into research and academic writing, offering opportunities to streamline workflows and increase productivity. However, these tools also introduce risks when used uncritically, unethically, or without transparency. In particular, the undisclosed use of GenAI, now widely documented, may compromise research integrity. The ai...
PURPOSE: To develop and validate a neural network-based Kid's Listening Performance Checklist (KLiP) for early identification of listening difficultie...
BACKGROUND: The rapid integration of generative AI into scholarly writing has created an inconsistent policy landscape, challenging academic integrity...
OBJECTIVES: To systematically review the evidence on the cost-effectiveness of artificial intelligence (AI) interventions for diagnostic imaging in ra...
INTRODUCTION: The use of Artificial Intelligence (AI) has grown dramatically in recent years. In addition to its use for data analysis, its applicatio...
BACKGROUND: Early temperament has been shown to predict socioemotional outcomes, but its neural correlates are not yet fully understood. In the curren...
BACKGROUND: A 24-hour urine collection is central to the metabolic evaluation and prevention of nephrolithiasis. Despite its widespread use, methodolo...
Liver tumor diagnosis relies heavily on imaging, and the liver imaging reporting and data system (LI-RADS) provides a structured framework for evaluat...
BACKGROUND: Large language models are increasingly being used in scientific writing, but their use in orthopaedic literature remains unclear. METHODS:...
This study examines the use of deepfakes in self-disclosure interventions within mental health contexts. Specifically, we investigate how videos featu...
PURPOSE: To evaluate the performance of a deep learning (DL) model based on graph isomorphism networks (GINs) for detecting glaucomatous visual field ...
BACKGROUND: Delirium is a common complication following cardiac surgery and significantly affects patient prognosis and quality of life. Recently, the...
OBJECTIVE: Reticular pseudodrusen (RPD) represent an important biomarker in age-related macular degeneration (AMD) but are difficult to grade and ofte...
OBJECTIVES: This study aimed to explore pediatric oncology nurses' perspectives on the integration of artificial intelligence (AI) into pediatric onco...
OBJECTIVE OR PURPOSE: To develop a lightweight neural network for automated cross-sectional and en face segmentation of ultra-widefield (UWF) OCT imag...
This study examines how CEO personality traits influence IPO risk disclosure quality. We employ a novel multimodal deep learning approach to measure C...
Echocardiography underpins the diagnosis and management of cardiovascular disease, yet measurement variability can influence treatment decisions. Arti...
PURPOSE: To develop an efficient approach to estimating visual field (VF) in patients with X-linked retinitis pigmentosa (RP) based on macular OCT sca...
PURPOSE: Novel large language models (LLMs) such as Generative Pretrained Transformer-5 (GPT-5) integrate advanced reasoning capabilities that may enh...