Latest AI and machine learning research in prevention of medical errors for healthcare professionals.
OBJECTIVES: Misdiagnosis of acute and chronic otitis media in children can result in significant consequences from either undertreatment or overtreatment. Our objective was to develop and train an artificial intelligence algorithm to accurately predict the presence of middle ear effusion in pediatric patients presenting to the operating room for myringotomy and tube placement.
Machine Learning (ML) is on the rise in medicine, promising improved diagnostic, therapeutic and prognostic clinical tools. While these technological innovations are bound to transform health care, they also bring new ethical concerns to the forefront. One particularly elusive challenge regards discriminatory algorithmic judgements based on biases inherent in the training data. A common line of re...
Online healthcare consultation offers people a convenient way to consult doctors. In this paper, we aim at building a generative dialog system for Chi...
Injuries have become devastating and often under-recognized public health concerns. In Canada, injuries are the leading cause of potential years of li...
With the development of the economy and technology, people's requirement for communication is also increasing. Satellite communication networks have b...
Forecasting patients' disease progressions with rich longitudinal clinical data has drawn much attention in recent years due to its impactful applicat...
BACKGROUND: Misdiagnosis, arbitrary charges, annoying queues, and clinic waiting times among others are long-standing phenomena in the medical industr...
Main aim of this study is to assess the effect of a structured, interdisciplinary, surgical, team-training protocol in robotic gynecologic surgery, wi...
In this work, we developed and validated a computer method capable of robustly detecting drill breakthrough events and show the potential of deep lear...
This article surveys reinforcement learning approaches in social robotics. Reinforcement learning is a framework for decision-making problems in which...
In recent years, public health emergencies have occurred frequently, posing a serious threat to the regional economy and the safety of people's lives ...
To identify the most important parameters associated with cerebral white matter hyperintensities (WMH), in consideration of potential collinearity, we...
Despite the availability of various diagnostic tests for inflammatory bowel diseases (IBD), misdiagnosis of IBD occurs frequently, and thus, there is ...
The most frequent extracranial solid tumors of childhood, named peripheral neuroblastic tumors (pNTs), are very challenging to diagnose due to their d...
The prevention of suicide and suicide-related behaviour are key policy priorities in Australia and internationally. The World Health Organization has ...
BACKGROUND: Anti-oxidants were investigated in several studies as a preventive strategy for prevention of contrast-induced nephropathy (CIN). Omega-3 ...
Glaucoma, the group of eye diseases is characterized by increased intraocular pressure, optic neuropathy and visual field defect patterns. Early and c...
Incidence and mortality rates of endometrial cancer are increasing, leading to increased interest in endometrial cancer risk prediction and stratifica...
Respiratory diseases are currently considered to be amongst the most frequent causes of death and disability worldwide, and even more so during the ye...
Industrial Internet of Things (IIoT) ensures reliable and efficient data exchanges among the industrial processes using Artificial Intelligence (AI) w...