115 resultados para Lacrimal duct obstruction diagnosis
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This paper proposes a highly reliable fault diagnosis approach for low-speed bearings. The proposed approach first extracts wavelet-based fault features that represent diverse symptoms of multiple low-speed bearing defects. The most useful fault features for diagnosis are then selected by utilizing a genetic algorithm (GA)-based kernel discriminative feature analysis cooperating with one-against-all multicategory support vector machines (OAA MCSVMs). Finally, each support vector machine is individually trained with its own feature vector that includes the most discriminative fault features, offering the highest classification performance. In this study, the effectiveness of the proposed GA-based kernel discriminative feature analysis and the classification ability of individually trained OAA MCSVMs are addressed in terms of average classification accuracy. In addition, the proposedGA- based kernel discriminative feature analysis is compared with four other state-of-the-art feature analysis approaches. Experimental results indicate that the proposed approach is superior to other feature analysis methodologies, yielding an average classification accuracy of 98.06% and 94.49% under rotational speeds of 50 revolutions-per-minute (RPM) and 80 RPM, respectively. Furthermore, the individually trained MCSVMs with their own optimal fault features based on the proposed GA-based kernel discriminative feature analysis outperform the standard OAA MCSVMs, showing an average accuracy of 98.66% and 95.01% for bearings under rotational speeds of 50 RPM and 80 RPM, respectively.
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An automated melanoma diagnosis system, the so-called Skin Polar-probe, was developed to improve the chances of early detection of skin cancers and help save the lives of melanoma victims. The system will offer unique benefits to aid early detection of melanoma - the key to reducing deaths caused by this cancer.
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Background: The existence of an ecstasy dependence syndrome is controversial. We examined whether the acute after-effects of ecstasy use (i.e., the “come-down”) falsely lead to the identification of ecstasy withdrawal and the subsequent diagnosis of ecstasy dependence. Methods: The Structured Clinical Interview for DSM-IV-TR Disorders: Research Version (SCID-RV) was administered to 214 Australian ecstasy users. Ecstasy withdrawal was operationalized in three contrasting ways: (i) as per DSM-IV criteria; (ii) as the expected after effects of ecstasy (a regular come-down); or (iii) as a substantially greater or longer come-down than on first use (intense come-down). These definitions were validated against frequency of ecstasy use, readiness to change and ability to resist the urge to use ecstasy. Confirmatory factor analyses were used to see how they aligned with the overall dependence syndrome. Results: Come-down symptoms increased the prevalence of withdrawal from 1% (DSM-IV criterion) to 11% (intense come-downs) and 75% (regular come-downs). Past year ecstasy dependence remained at 31% when including the DSM-IV withdrawal criteria and was 32% with intense come-downs, but increased to 45% with regular come-downs. Intense come-downs were associated with lower ability to resist ecstasy use and loaded positively on the dependence syndrome. Regular come-downs did not load positively on the ecstasy dependence syndrome and were not related to other indices of dependence. Conclusion: The acute after-effects of ecstasy should be excluded when assessing ecstasy withdrawal as they can lead to a false diagnosis of ecstasy dependence. Worsening of the ecstasy come-down may be a marker for dependence.
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An increasing amount of people seek health advice on the web using search engines; this poses challenging problems for current search technologies. In this paper we report an initial study of the effectiveness of current search engines in retrieving relevant information for diagnostic medical circumlocutory queries, i.e., queries that are issued by people seeking information about their health condition using a description of the symptoms they observes (e.g. hives all over body) rather than the medical term (e.g. urticaria). This type of queries frequently happens when people are unfamiliar with a domain or language and they are common among health information seekers attempting to self-diagnose or self-treat themselves. Our analysis reveals that current search engines are not equipped to effectively satisfy such information needs; this can have potential harmful outcomes on people’s health. Our results advocate for more research in developing information retrieval methods to support such complex information needs.
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In this paper, we propose a highly reliable fault diagnosis scheme for incipient low-speed rolling element bearing failures. The scheme consists of fault feature calculation, discriminative fault feature analysis, and fault classification. The proposed approach first computes wavelet-based fault features, including the respective relative wavelet packet node energy and entropy, by applying a wavelet packet transform to an incoming acoustic emission signal. The most discriminative fault features are then filtered from the originally produced feature vector by using discriminative fault feature analysis based on a binary bat algorithm (BBA). Finally, the proposed approach employs one-against-all multiclass support vector machines to identify multiple low-speed rolling element bearing defects. This study compares the proposed BBA-based dimensionality reduction scheme with four other dimensionality reduction methodologies in terms of classification performance. Experimental results show that the proposed methodology is superior to other dimensionality reduction approaches, yielding an average classification accuracy of 94.9%, 95.8%, and 98.4% under bearing rotational speeds at 20 revolutions-per-minute (RPM), 80 RPM, and 140 RPM, respectively.
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Aim To document current practice by dietitians in Australia and Canada in the nutrition management of Parkinson's disease. This will help identify priority areas for review and development of practice guidelines and direct future research. Methods Current practice in the phases of the Nutrition Care Plan was captured using an online survey distributed to Dietitians Association of Australia members and Practice-Based Evidence in Nutrition subscribers through their email newsletters. The results of the diagnosis, intervention and monitoring phases are presented here. Results Eighty-four dietitians responded. There was consistency in practice for nutrition issues that are encountered in other populations, such as malnutrition and constipation. There was more variation in practice in the nutrition issues that are more specific to Parkinson's disease, such as nutrition and meal interactions with medication. A lack of awareness of emerging treatments, such as deep brain stimulation surgery, appears to exist in the responding dietitians. Conclusions The variation in practice that was present for the nutrition issues specific to Parkinson's disease may reflect the lack of quality evidence and subsequently evidence-based guidelines in these areas. Work to provide background information about treatment options and to translate current evidence for the nutrition issues that are specific to Parkinson's disease into practice recommendations should be completed.
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Best practice dictates that the Autism Spectrum Disorder (ASD) diagnostic process is informed by experienced professionals from at least two disciplines, for example psychology or speech pathology, with the diagnosis ultimately provided by a specialist medical practitioner e.g. child psychiatrist, neurologist or paediatrician. Irrespective of a child’s age, diagnosis relies upon information about their early development. Current information and observations on a child’s behaviour, communication and socialisation are considered by the specialist medical practitioner against the signs and symptoms detailed in one of several diagnostic systems. Two recently used classification systems in Australia have been the fourth edition of the Diagnostic Statistical Manual of Mental Disorders (DSM-IV) published by the American Psychiatric Association (1994) and the tenth edition of the International Classification of Disease (ICD-10), published by the World Health Organisation (2003).
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Disclosed are methods for detecting the presence of a carcinoma or an increased likelihood that a carcinoma is present in a subject. More particularly, the present invention discloses methods for diagnosis, screening, treatment and monitoring of carcinomas associated with aberrant DNA methylation of the MED15 promoter region
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Human papilloma virus (HPV) infection is a major risk factor for a distinct subset of head and neck squamous cell carcinoma (HNSCC). The current review summarizes the epidemiology of HNSCC and the disease burden, the infectious cycle of HPV, the roles of viral oncoproteins, E6 and E7, and the downstream cellular events that lead to malignant transformation. Current techniques for the clinical diagnosis of HPV-associated HNSCC will also be discussed, that is, the detection of HPV DNA, RNA, and the HPV surrogate marker, p16 in tumor tissues, as well as HPV-specific antibodies in serum. Such methods do not allow for the early detection of HPV-associated HNSCC and most cases are at an advanced stage upon diagnosis. Novel noninvasive approaches using oral fluid, a clinically relevant biological fluid, allow for the detection of HPV and cellular alterations in infected cells, which may aid in the early detection and HPV-typing of HNSCC tumors. Noninvasive diagnostic methods will enable early detection and intervention, leading to a significant reduction in mortality and morbidity associated with HNSCC.
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Rolling-element bearing failures are the most frequent problems in rotating machinery, which can be catastrophic and cause major downtime. Hence, providing advance failure warning and precise fault detection in such components are pivotal and cost-effective. The vast majority of past research has focused on signal processing and spectral analysis for fault diagnostics in rotating components. In this study, a data mining approach using a machine learning technique called anomaly detection (AD) is presented. This method employs classification techniques to discriminate between defect examples. Two features, kurtosis and Non-Gaussianity Score (NGS), are extracted to develop anomaly detection algorithms. The performance of the developed algorithms was examined through real data from a test to failure bearing. Finally, the application of anomaly detection is compared with one of the popular methods called Support Vector Machine (SVM) to investigate the sensitivity and accuracy of this approach and its ability to detect the anomalies in early stages.
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Carbon nanostructures (CNs) are amongst the most promising biorecognition nanomaterials due to their unprecedented optical, electrical and structural properties. As such, CNs may be harnessed to tackle the detrimental public health and socio-economic adversities associated with neurodegenerative diseases (NDs). In particular, CNs may be tailored for a specific determination of biomarkers indicative of NDs. However, the realization of such a biosensor represents a significant technological challenge in the uniform fabrication of CNs with outstanding qualities in order to facilitate a highly-sensitive detection of biomarkers suspended in complex biological environments. Notably, the versatility of plasma-based techniques for the synthesis and surface modification of CNs may be embraced to optimize the biorecognition performance and capabilities. This review surveys the recent advances in CN-based biosensors, and highlights the benefits of plasma-processing techniques to enable, enhance, and tailor the performance and optimize the fabrication of CNs, towards the construction of biosensors with unparalleled performance for the early diagnosis of NDs, via a plethora of energy-efficient, environmentally-benign, and inexpensive approaches.
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• As part of the 3E program, we conducted a systematic literature review and gathered consensus from 23 practising Australian rheumatologists to develop guidelines for early identification of ankylosing spondylitis and specialist referral. • In three rounds of break-out sessions followed by discussion and voting, the specialist panel addressed three questions related to diagnosis of ankylosing spondylitis: In individuals with back pain, what are the early clinical features that suggest ankylosing spondylitis? How useful is imaging in identifying early ankylosing spondylitis? Based on which clinical features should a general practitioner refer a patient to a rheumatologist for further evaluation? • The panel agreed on six recommendations related to the three questions: 1a. Early clinical features to suggest ankylosing spondylitis include inflammatory back pain and age at symptom onset < 45 years. 1b. The absence of symptomatic response to an appropriate course of non-steroidal anti-inflammatory drugs makes the diagnosis of ankylosing spondylitis less likely. 1c. Raised inflammatory markers are supportive, but their absence does not rule out the diagnosis of ankylosing spondylitis. 2a. Despite low sensitivity to detect changes of early ankylosing spondylitis, plain radiographs of the pelvis and spine are appropriate initial imaging techniques. 2b. Magnetic resonance imaging is a useful imaging modality for detecting early changes of ankylosing spondylitis. 3. Individuals with inflammatory back pain should be referred to a rheumatologist for further evaluation. • Effective dissemination and implementation of these recommendations are important to standardise the approach to early diagnosis of ankylosing spondylitis.
Evaluation of growth and changes in body composition following neonatal diagnosis of cystic fibrosis
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Early deficits in nutritional status that might require specific treatment and early response to nutritional therapy were studied longitudinally in 25 infants with cystic fibrosis (CF) diagnosed by neonatal screening, using anthropometric and research body composition methodology, and evaluation of pancreatic function. At the time of confirmed diagnosis (mean 5.4 weeks), body mass, length, total body fat (TBF), and total body potassium (TBK) were all significantly reduced. Following diagnosis and commencement of therapy there was a normalization of weight, length, and TBK by 6-12 months of age, indicating catch-up growth. But in some individuals the response was incomplete, and as a group, mean total body fat remained significantly lower than normal at 1 year of age. Seven of 25 (28%) were pancreatic sufficient at diagnosis, and all but one had evidence of declining pancreatic function requiring the institution of pancreatic enzyme therapy during the next 1-9 months. The median age of commencement of enzyme therapy was 10 weeks (range 5 weeks to 11 months). These longitudinal assessments emphasize the dynamic changes occurring in absorptive function, body composition, and nutritional status following neonatal diagnosis of cystic fibrosis and may reflect previously described abnormalities of energy metabolism in this age group. Abnormal body composition is evident in most CF infants following diagnosis by neonatal screening but pancreatic damage may still be evolving. We suggest that early active nutritional therapy and surveillance for changes in pancreatic function are warranted in CF infants diagnosed by neonatal screening.