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Publications (36)
Accurate in-hospital length of stay prediction is a vital quality metric for hospital leaders and health policy decision-makers. It assists with decision-making and informs hospital operations involving factors such as patient flow, elective cases, and human resources allocation, while also informing quality of care and risk considerations. The aim...
Accurate in-hospital length of stay prediction is a vital quality metric for hospital leaders and health policy decision-makers. It assists with decision-making and informs hospital operations involving factors such as patient flow, elective cases, and human resources allocation, while also informing quality of care and risk considerations. The aim...
Research on email anomaly detection has typically relied on specially prepared datasets that may not adequately reflect the type of data that occurs in industry settings. In our research, at a major financial services company, privacy concerns prevented inspection of the bodies of emails and attachment details (although subject headings and attachm...
In this paper we consider the problem of defending against increasing data exfiltration threats in the domain of cybersecurity. We review existing work on exfiltration threats and corresponding countermeasures. We consider current problems and challenges that need to be addressed to provide a qualitatively better level of protection against data ex...
![Fig. 3. The USB file transfer volume dashboard (Fig. 3 in Ref. [30]).](profile/Mark-Chignell/publication/367193449/figure/fig2/AS:11431281114031728@1674217601214/The-USB-file-transfer-volume-dashboard-Fig-3-in-Ref-30_Q320.jpg)
Employees who have legitimate access to an organization's data may occasionally put sensitive corporate data at risk, either carelessly or maliciously. Ideally, potential breaches should be detected as soon as they occur, but in practice there may be delays, because human analysts are not able to recognize data exfiltration behaviors quickly enough...
We review HCI history from both the perspective of its 1980s split with human factors and its nature as a discipline. We then revisit human augmentation as an alternative to user friendliness that seems particularly relevant in the areas of inclusive design and artificial intelligence. Viewing human-AI interaction as a kind of human augmentation ra...
Delirium is an acute neurocognitive disorder, which is difficult to identify and predict. Using GEMINI, Canada's largest hospital data and analytics study, we had a labeled sample of around 4,000 cases with approximately 25% of cases being labeled as having delirium. Based on this labeled data, we developed machine learning (ML) models and interact...
Background
Delirium is an acute neurocognitive disorder that affects up to half of older hospitalized medical patients and can lead to dementia, longer hospital stays, increased health costs, and death. Although delirium can be prevented and treated, it is difficult to identify and predict.
Objective
This study aimed to improve machine learning mo...
Many real-world datasets are labeled with natural orders, i.e., ordinal labels. Ordinal regression is a method to predict ordinal labels that finds a wide range of applications in data-rich domains, such as natural, health and social sciences. Most existing ordinal regression approaches work well for independent and identically distributed (IID) in...
While many machine learning methods have been used for medical prediction and risk factor analysis on healthcare data, most prior research has involved single-task learning (STL) methods. However, healthcare research often involves multiple related tasks. For instance, implementation of disease scores prediction and risk factor analysis in multiple...
Many real-world datasets are labeled with natural orders, i.e., ordinal labels. Ordinal regression is a method to predict ordinal labels that finds a wide range of applications in data-rich science domains, such as medical, social and economic sciences. Most existing approaches work well for a single ordinal regression task. However, they ignore th...
There are many major diseases that remain incurable, such as cancer and Alzheimer’s disease (AD). Therefore, the prevention for these diseases has more impact than diagnosis and treatment. Survival analysis aims at predicting the time of occurrence of specific events of interest. It can be used to identify patients of high risk, which helps healthc...
Graphene oxide (GO) is one of the most important ceramic-toughening candidates due to its outstanding physical and chemical properties. In this paper, nacre-like alumina ceramics reinforced with GO have been prepared by freeze casting followed by hot pressing. The experimental results showed that a laminated structure with homogeneous distribution...
Hydrocyclone-induced pretreatment was first proposed for sludge disintegration to address excess sludge and to be served as a means of sustainable energy production. The effects of hydrocyclone disintegration alone and combination of hydrocyclone and alkaline pretreatments on sludge solubilization followed by anaerobic digestion were investigated....
NiFe2O4 powders were synthesized by a facile hydrothermal method at 180°C followed by a thermal treatment at 300°C. The phase composition and morphology were analyzed by X-ray diffraction (XRD) and scanning electron microscope (SEM). The results showed that the NiFe2O4 powders were well-crystallized, and they possessed a particle size in the range...
A method to synthesize boron nitride (BN) coating on the surface of graphene has been developed. BN coating was synthesized by the direct reaction of sodium borohydride and ammonium chloride at a relatively low temperature of 600 °C. Synthesized sample was characterized by RAM, XRD, FESEM, TEM and XPS. It is revealed that the BN coating combines wi...
Due to the remarkable physical and mechanical properties of graphene, it is considered to be one of the most promising reinforcements for structural ceramics. In this paper, the composite material is compacted by hot pressing and the effects of mechanical stirring and ultrasonic on dispersion of graphene in alumina matrix were investigated, which w...
Despite many data clustering methods are available, most of them uncover compactness or connectivity as the intrinsic structure of unlabeled data. Very few approaches explicitly consider the cluster size distribution, especially over-dispersed (high variance), which may represent yet another important aspect of structural information of unlabeled d...
Background
Precision medicine approach holds great promise to tailored diagnosis, treatment and prevention. Individuals can be vastly different in their genomic information and genetic mechanisms hence having unique transcriptomic signatures. The development of precision medicine has demanded moving beyond DNA sequencing (DNA-Seq) to much more poin...
A major computational challenge in analyzing metagenomics sequencing reads is to identify unknown sources of massive and heterogeneous short DNA reads. A promising approach is to efficiently and sufficiently extract and exploit sequence features, i.e., k-mers, to bin the reads according to their sources. Shorter k-mers may capture base composition...
