Latest AI and machine learning research in risk management for healthcare professionals.
BACKGROUND: Acute chest pain (ACP) is one of the most common chief complaints in the emergency department (ED), accounting for approximately 8% of all ED visits. However, among patients presenting with chest pain suggestive of cardiac origin, fewer than 10% are ultimately diagnosed with acute coronary syndrome (ACS). OBJECTIVE: AI models were developed to support clinical decision-making for triag...
OBJECTIVE: To predict patient satisfaction 6 months after small-incision lenticule extraction (SMILE) surgery from preoperative clinical data demonstrating the methodological utility of open-source orange data mining software (Orange) feature selection and machine learning (ML) for practice-based evidence. DESIGN: A retrospective study. PARTICIPANTS: Seventy-eight patients who had undergone bilate...
INTRODUCTION: Fracture misdiagnosis is a common diagnostic error in emergency departments (EDs) and minor injury units (MIUs), leading to poor patient...
Large language models (LLMs) and agents have lately propelled advances in artificial intelligence for science (AI4S). In this work, we propose a tools...
Perioperative anaesthetic complications are a major public health concern, as they are associated with increased mortality, prolonged hospital stay, h...
OBJECTIVES: Artificial intelligence (AI) and machine learning applications are rapidly expanding across healthcare. Successful implementation of AI te...
INTRODUCTION: The creation of simulation scenarios is typically time-consuming and requires a high cognitive load. Artificial intelligence (AI) and la...
BACKGROUND: Preserving functional independence is critical in older patients with heart failure (HF), yet tools predicting long-term functional trajec...
Human Activity Recognition (HAR) using wearable sensors is relevant to rehabilitation, assistive robotics, and mobile health applications. This study ...
The recent integration of artificial intelligence (AI) into academia could usher in transformative efficiencies across scholarly workflows-from manusc...
To address the limitations of existing non-interactive protocol state machine inference methods in feature representation capability, inter-stage info...
OBJECTIVES: A substantial proportion of adults with locally advanced gastric cancer derive limited benefit from neoadjuvant chemotherapy (NAC), with a...
PURPOSE: The transition toward competency-based medical education requires scalable, objective surgical skill assessment. While sensor-based approache...
BACKGROUND: Gait impairment is a prevalent sequela of stroke. Although observational gait analysis remains a standard clinical practice for assessing ...
RATIONALE AND OBJECTIVES: Hospital-radiology joint ventures (JVs) are forming at an accelerating pace as health systems seek to recapture outpatient i...
This study aims to provide rapid and precise methods for industrial users to predict the amount of sewing thread required to sew garments using differ...
Strategic Management instruction requires students to apply analytical frameworks to uncertain, resource-constrained, and trade-off-based business sit...
Generative artificial intelligence (AI) is beginning to reshape medical research, with ophthalmology at the forefront of this transformation. This nar...
PURPOSE: To evaluate ChatGPT-4o in a real-world urological multidisciplinary tumour board (MTB), with concordance for the final clinical recommendatio...
BACKGROUND: Advanced HIV disease remains a major global health concern, with nearly 40.8 million people living with HIV as of 2024. Antiretroviral the...