Singapore medical journal
-
Singapore medical journal · May 2023
A machine learning approach for the diagnosis of obstructive sleep apnoea using oximetry, demographic and anthropometric data.
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. Machine learning (ML) models have strengths in disease prediction and early diagnosis. We explored the use of ML with oximetry, demographic and anthropometric data to diagnose OSA. ⋯ Our study showed that the prediction of moderate-severe OSA in a tertiary setting with an ML approach is a viable option to facilitate early identification of OSA. Prospective studies with home-based oximeters and analysis of other oximetry variables are the next steps towards formal implementation.
-
Singapore medical journal · May 2023
Oncology-related emergencies discharged from the emergency department.
Cancer patients attending emergency departments (EDs) often present with acute symptoms and are frequently admitted. This study aimed to characterise the profile of oncology patients who were discharged from the ED. ⋯ Selected oncological patients may potentially be managed in an ambulatory setting.