AI Medical Compendium Journal:
Singapore medical journal

Showing 1 to 10 of 15 articles

Deploying artificial intelligence in the detection of adult appendicular and pelvic fractures in the Singapore emergency department after hours: efficacy, cost savings and non-monetary benefits.

Singapore medical journal
INTRODUCTION: Radiology plays an integral role in fracture detection in the emergency department (ED). After hours, when there are fewer reporting radiologists, most radiographs are interpreted by ED physicians. A minority of these interpretations ma...

Ethics of artificial intelligence in medicine.

Singapore medical journal
This article reviews the main ethical issues that arise from the use of artificial intelligence (AI) technologies in medicine. Issues around trust, responsibility, risks of discrimination, privacy, autonomy, and potential benefits and harms are asses...

Artificial intelligence-based video monitoring of movement disorders in the elderly: a review on current and future landscapes.

Singapore medical journal
Due to global ageing, the burden of chronic movement and neurological disorders (Parkinson's disease and essential tremor) is rapidly increasing. Current diagnosis and monitoring of these disorders rely largely on face-to-face assessments utilising c...

Development and validation of a deep learning system for detection of small bowel pathologies in capsule endoscopy: a pilot study in a Singapore institution.

Singapore medical journal
INTRODUCTION: Deep learning models can assess the quality of images and discriminate among abnormalities in small bowel capsule endoscopy (CE), reducing fatigue and the time needed for diagnosis. They serve as a decision support system, partially aut...

Use of deep learning model for paediatric elbow radiograph binomial classification: initial experience, performance and lessons learnt.

Singapore medical journal
INTRODUCTION: In this study, we aimed to compare the performance of a convolutional neural network (CNN)-based deep learning model that was trained on a dataset of normal and abnormal paediatric elbow radiographs with that of paediatric emergency dep...

A machine learning approach for the diagnosis of obstructive sleep apnoea using oximetry, demographic and anthropometric data.

Singapore medical journal
INTRODUCTION: Obstructive sleep apnoea (OSA) is a serious but underdiagnosed condition. Demand for the gold standard diagnostic polysomnogram (PSG) far exceeds its availability. More efficient diagnostic methods are needed, even in tertiary settings....