Objective: To analyze the Multidimensional Health Assessment Questionnaire (MDHAQ) in screening for anxiety in patients with rheumatoid arthritis (RA) and psoriatic arthritis (PsA), compared to the Hospital Anxiety and Depression Scale (HADS) as the reference standard.
Methods: Patients with a physician diagnosis of RA or PsA were invited to complete the MDHAQ and HADS at their routine rheumatology clinic visit. Sensitivity, specificity, percent agreement, and [Formula: see text] statistics were used to evaluate agreement between 2 MDHAQ items for anxiety and HADS subscale for Anxiety (HADS-A) score of ≥ 8.
This paper studies how counterfactual explanations can be used to assess the fairness of a model. Using machine learning for high-stakes decisions is a threat to fairness as these models can amplify bias present in the dataset, and there is no consensus on a universal metric to detect this. The appropriate metric and method to tackle the bias in a dataset will be case-dependent, and it requires insight into the nature of the bias first.
View Article and Find Full Text PDFAlthough varicella-zoster virus (VZV) is known to affect the central nervous system in a protean manner, hemorrhagic VZV meningitis has not been well documented in the literature. Here, we correlate the clinical, cytologic, and radiologic findings in an immunocompromised patient presenting with subarachnoid hemorrhage associated with VZV meningitis. Clinical findings included multidermatomal zoster, myelitis, and neurapraxia.
View Article and Find Full Text PDFIntroduction: Long waiting time is an important barrier to accessing recommended care for low back pain (LBP) in Australia's public health system. This study describes the protocol for a randomised controlled trial (RCT) that aims to establish the feasibility of delivering and evaluating stratified care integrated with telehealth ('Rapid Stratified Telehealth'), which aims to reduce waiting times for LBP.
Methods And Analysis: We will conduct a single-centre feasibility and pilot RCT with nested qualitative interviews.
Annu Int Conf IEEE Eng Med Biol Soc
July 2019
Detecting critical events in postoperative care and improving comfort, costs and availability in sleep assessment are two of many areas in which wearable biosignal acquisition can be a viable tool. Modern sensors as well as patch and textile integration facilitate unobtrusive biosignal acquisition, yet placing sensors at different locations across the body is still prevailing. Actigraphy and the electrocardiogram (ECG) are commonly integrated modalities.
View Article and Find Full Text PDFThe outstanding performance of deep learning (DL) for computer vision and natural language processing has fueled increased interest in applying these algorithms more broadly in both research and practice. This study investigates the application of DL techniques to classification of large sparse behavioral data-which has become ubiquitous in the age of big data collection. We report on an extensive search through DL architecture variants and compare the predictive performance of DL with that of carefully regularized logistic regression (LR), which previously (and repeatedly) has been found to be the most accurate machine learning technique generally for sparse behavioral data.
View Article and Find Full Text PDFObjective: To establish whether the use of ultrasound to direct shock waves to the area of greater calcification in calcaneal enthesopathies was more effective than the common procedure of directing shock waves to the point where the patient has the most tenderness.
Design: Two-armed nonblinded randomized control trial with allocation concealment.
Setting: The Sports Clinic at Sydney University.
Many of the state-of-the-art data mining techniques introduce nonlinearities in their models to cope with complex data relationships effectively. Although such techniques are consistently included among the top classification techniques in terms of predictive power, their lack of transparency renders them useless in any domain where comprehensibility is of importance. Rule-extraction algorithms remedy this by distilling comprehensible rule sets from complex models that explain how the classifications are made.
View Article and Find Full Text PDFWith the increasingly widespread collection and processing of "big data," there is natural interest in using these data assets to improve decision making. One of the best understood ways to use data to improve decision making is via predictive analytics. An important, open question is: to what extent do larger data actually lead to better predictive models? In this article we empirically demonstrate that when predictive models are built from sparse, fine-grained data-such as data on low-level human behavior-we continue to see marginal increases in predictive performance even to very large scale.
View Article and Find Full Text PDFIEEE Trans Neural Netw
December 2011
Previous research has shown that sex differences exist in the composition of lateral movements (E. F. Field, I.
View Article and Find Full Text PDFAdult stem cells in various tissues are relatively quiescent. The cell cycle inhibitor p21cip1/waf1 (p21) has been shown to be important for maintaining hematopoietic stem cell quiescence and self-renewal. We examined the role of p21 in the regulation of adult mammalian forebrain neural stem cells (NSCs).
View Article and Find Full Text PDFStem cells isolated from the fourth ventricle and spinal cord form neurospheres in vitro in response to basic fibroblast growth factor (FGF2)+heparin (H) or epidermal growth factor (EGF)+FGF2 together. To determine whether these growth factor conditions are sufficient to induce stem cells within the fourth ventricle and spinal cord to proliferate and expand their progeny in vivo, we infused EGF and FGF2, alone or together, with or without H, into the fourth ventricle for 6 days via osmotic minipumps. Animals were injected with bromodeoxyuridine (BrdU) on days 4, 5 and 6 of infusion in order to label cells proliferating in response to the growth factors.
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