Risk Prediction of a Multiple Sclerosis Diagnosis

Multiple sclerosis (MS) is a chronic autoimmune disease that affects the central nervous system. The progression and severity of MS varies by individual, but it is generally a disabling disease. Although medications have been developed to slow the disease progression and help manage symptoms, MS research has yet to result in a cure. Early diagnosis and treatment of the disease have been shown to be effective at slowing the development of disabilities. However, early MS diagnosis is difficult because symptoms are intermittent and shared with other diseases. Thus most previous works have focused on uncovering the risk factors associated with MS and predicting the progression of disease after a diagnosis rather than disease prediction. This paper investigates the use of data available in electronic medical records (EMRs) to create a risk prediction model; thereby helping clinicians perform the difficult task of diagnosing an MS patient. Our results demonstrate that even given a limited time window of patient data, one can achieve reasonable classification with an area under the receiver operating characteristic curve of 0.724. By restricting our features to common EMR components, the developed models also generalize to other healthcare systems

Examination of square-wave modulated voltage dip restorer and its harmonics analysis

Author name used in this publication: S. L. HoAuthor name used in this publication: K. W. E. Cheng2006-2007 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Return to work after stroke in Hong Kong. Part 2: a psychosocial perspective

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Investigation of voltage dip restorer using square wave inverter

Author name used in this publication: K. W. E. ChengAuthor name used in this publication: S. L. HoAuthor name used in this publication: K. P. WongRefereed conference paper2004-2005 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Return to work after stroke in Hong Kong. Part 1: a biological perspective

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Prediction of recovery of swallowing disorder in stroke patients after rehabilitation

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Haemorrhagic stroke vs ischaemic stroke: length of stay and functional outcome measures in stroke survivors

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Outcome of neurogenic dysphagia in stroke patients

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Self-help cognitive-behavioral therapy for insomnia (CBT-1): a systematic review of randomized controlled trials

Abstract Theme: Insomnia - new insight into development and manageThis study aimed to review current literature, examine the efficacy, adherence, acceptability, and attrition rate of self-help CBT-I, and to explore possible factors that might contribute to the effectiveness of the treatment. A systematic review was performed up to June 2012 on studies published in 6 major electronic databases. Two researchers performed study identification, data extraction, and methodological quality evaluation. Meta-analyses of self-help CBT-I vs. waiting-list, routine care, or no treatment, therapist-administered CBT-I, and placebo treatment were performed. We identified 20 randomized controlled trials (RCT) that met inclusion criteria. When compared to waiting-list control, self-help CBT-I achieved a moderate to large effect size on improving sleep and reducing sleep-related cognitions and anxiety and depressive symptoms. Therapist-administered CBT-I was slightly better than self-help CBT-I. Subgroup analyses supported the beneficial effect of telephone consultation, but not for “full” multi-component CBT and programs lasting for 6 or more weeks. Treatment adherence, acceptability, perceived usefulness, and credibility were reported as satisfactory. Based on the results of the systematic review, we have designed a Chinese-language self-help CBT-I and now conducting a RCT to evaluate the efficacy of Internet-based self-help CBT-I in Chinese population.postprin