36 research outputs found
Working with International Students in the U.S. and Beyond: A Summary of Survey Research by NCDA International Student Services Committee
The career development process is one of the most important aspects of the international student experience. Providing comprehensive and culturally competent services requires institutional efforts that utilize best practices developmentally throughout the college experience and beyond. This article is based on the work of the International Student Services Committee of the National Career Development Association, especially the surveys conducted with international students, career development professional and employers. The authors focus on three major themes from the surveys: knowledge about work authorization options, impact of cultural differences on job search, and specialized career services for international students. Discussing these major themes, the authors report on best practices and future implications for supporting international student career development in the U.S. and beyond
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Combining macula clinical signs and patient characteristics for age-related macular degeneration diagnosis: a machine learning approach
Background: To investigate machine learning methods, ranging from simpler interpretable techniques to complex (non-linear) “black-box” approaches, for automated diagnosis of Age-related Macular Degeneration (AMD).
Methods: Data from healthy subjects and patients diagnosed with AMD or other retinal diseases were collected during routine visits via an Electronic Health Record (EHR) system. Patients’ attributes included demographics and, for each eye, presence/absence of major AMD-related clinical signs (soft drusen, retinal pigment epitelium, defects/ pigment mottling, depigmentation area, subretinal haemorrhage, subretinal fluid, macula thickness, macular scar, subretinal fibrosis). Interpretable techniques known as white box methods including logistic regression and decision trees as well as less interpreitable techniques known as black box methods, such as support vector machines (SVM), random forests and AdaBoost, were used to develop models (trained and validated on unseen data) to diagnose AMD. The gold standard was confirmed diagnosis of AMD by physicians. Sensitivity, specificity and area under the receiver operating characteristic (AUC) were used to assess performance.
Results: Study population included 487 patients (912 eyes). In terms of AUC, random forests, logistic regression and adaboost showed a mean performance of (0.92), followed by SVM and decision trees (0.90). All machine learning models identified soft drusen and age as the most discriminating variables in clinicians’ decision pathways to diagnose AMD. C
Conclusions: Both black-box and white box methods performed well in identifying diagnoses of AMD and their decision pathways. Machine learning models developed through the proposed approach, relying on clinical signs identified by retinal specialists, could be embedded into EHR to provide physicians with real time (interpretable) support
A mobile-health system to manage Chronic Obstructive Pulmonary Disease patients at home
Chronic Obstructive Pulmonary Disease (COPD) is a major cause of morbidity and mortality in Australia and globally, and leads to a substantial burden on healthcare services. Effective and timely management of patients with COPD has been essential to alleviate COPD exacerbation, improve the quality of life, and consequently reduce the economic burden. To achieve this, a mobile and internet technologies assisted home care model (M-COPD) was developed to assist clinicians to remotely monitor and manage COPD conditions and events. This paper will focus on the technical aspect of M-COPD system by describing its setup and discussing how the M-COPD could address the clinical needs in monitoring and managing COPD conditions of patients at home
Ocular Biomarkers of Alzheimer's Disease: The Role of Anterior Eye and Potential Future Directions
Globally, Alzheimer's disease (AD) is a growing health and economic challenge that has no effective cure. Recent clinical trials indicate that preclinical treatment may be required but a routine screening tool for AD has been elusive. Hence, a simple, yet sensitive biomarker for preclinical AD, when the disease is most likely to be amenable to treatment, is lacking. Due to several features, the eye has been explored for this purpose and, among the ocular tissues, the retina has received the most attention. Currently, major works investigating the potential AD diagnosis by detecting amyloid-β (Aβ) signatures in the retinal tissue are underway, while the anterior eye is more accessible for in vivo imaging and examination. This report provides a concise review of current literature on the anterior eye components, including the crystalline lens, cornea, and aqueous humor, in AD. We also discuss the potential for assessment of the corneal nerve structure and regeneration as well as conjunctival tissue for AD-related alterations. The crystalline lens has received considerable attention, but further research is required to confirm whether Aβ accumulates in the lens and whether it mirrors brain neuropathologic changes, particularly in preclinical AD. The rich corneal neural network and conjunctival vasculature also merit exploration in future studies to shed light on their potential association with AD pathologic changes
Evaluation of cholinergic deficiency in preclinical Alzheimer’s disease using pupillometry
Cortical cholinergic deficiency is prominent in Alzheimer's disease (AD), and published findings of diminished pupil flash response in AD suggest that this deficiency may extend to the visual cortical areas and anterior eye. Pupillometry is a low-cost, noninvasive technique that may be useful for monitoring cholinergic deficits which generally lead to memory and cognitive disorders. The aim of the study was to evaluate pupillometry for early detection of AD by comparing the pupil flash response (PFR) in AD (N = 14) and cognitively normal healthy control (HC, N = 115) participants, with the HC group stratified according to high (N = 38) and low (N = 77) neocortical amyloid burden (NAB). Constriction phase PFR parameters were significantly reduced in AD compared to HC (maximum acceleration p < 0.05, maximum velocity p < 0.0005, average velocity p < 0.005, and constriction amplitude p < 0.00005). The high-NAB HC subgroup had reduced PFR response cross-sectionally, and also a greater decline longitudinally, compared to the low-NAB subgroup, suggesting changes to pupil response in preclinical AD. The results suggest that PFR changes may occur in the preclinical phase of AD. Hence, pupillometry has a potential as an adjunct for noninvasive, cost-effective screening for preclinical AD
Retinal vascular biomarkers for early detection and monitoring of Alzheimer’s disease
The earliest detectable change in Alzheimer’s disease (AD) is the buildup of amyloid plaque in the brain. Early detection of AD, prior to irreversible neurological damage, is important for the efficacy of current interventions as well as for the development of new treatments. Although PiB-PET imaging and CSF amyloid are the gold standards for early AD diagnosis, there are practical limitations for population screening. AD-related pathology occurs primarily in the brain, but some of the hallmarks of the disease have also been shown to occur in other tissues, including the retina, which is more accessible for imaging. Retinal vascular changes and degeneration have previously been reported in AD using optical coherence tomography and laser Doppler techniques. This report presents results from analysis of retinal photographs from AD and healthy control participants from the Australian Imaging, Biomarkers and Lifestyle (AIBL) Flagship Study of Ageing. This is the first study to investigate retinal blood vessel changes with respect to amyloid plaque burden in the brain. We demonstrate relationships between retinal vascular parameters, neocortical brain amyloid plaque burden and AD. A number of RVPs were found to be different in AD. Two of these RVPs, venular branching asymmetry factor and arteriolar length-to-diameter ratio, were also higher in healthy individuals with high plaque burden (P=0.01 and P=0.02 respectively, after false discovery rate adjustment). Retinal photographic analysis shows potential as an adjunct for early detection of AD or monitoring of AD-progression or response to treatments
Evaluation of Cholinergic Deficiency in Preclinical Alzheimer's Disease Using Pupillometry
Cortical cholinergic deficiency is prominent in Alzheimer's disease (AD), and published findings of diminished pupil flash response in AD suggest that this deficiency may extend to the visual cortical areas and anterior eye. Pupillometry is a low-cost, noninvasive technique that may be useful for monitoring cholinergic deficits which generally lead to memory and cognitive disorders. The aim of the study was to evaluate pupillometry for early detection of AD by comparing the pupil flash response (PFR) in AD (N = 14) and cognitively normal healthy control (HC, N = 115) participants, with the HC group stratified according to high (N = 38) and low (N = 77) neocortical amyloid burden (NAB). Constriction phase PFR parameters were significantly reduced in AD compared to HC (maximum acceleration p < 0.05, maximum velocity p < 0.0005, average velocity p < 0.005, and constriction amplitude p < 0.00005). The high-NAB HC subgroup had reduced PFR response cross-sectionally, and also a greater decline longitudinally, compared to the low-NAB subgroup, suggesting changes to pupil response in preclinical AD. The results suggest that PFR changes may occur in the preclinical phase of AD. Hence, pupillometry has a potential as an adjunct for noninvasive, cost-effective screening for preclinical AD