Handwriting analysis for diagnosis and prognosis of Parkinson’s disease

At present, there are no quantitative, objective methods for diagnosing the Parkinson disease. Existing methods of quantitative analysis by myograms suffer by inaccuracy and patient strain; electronic tablet analysis is limited to the visible drawing, not including the writing forces and hand movements. In our paper we show how handwriting analysis can be obtained by a new electronic pen and new features of the recorded signals. This gives good results for diagnostics. Keywords: Parkinson diagnosis, electronic pen, automatic handwriting analysi

An Optimisation-Driven Prediction Method for Automated Diagnosis and Prognosis

open access articleThis article presents a novel hybrid classification paradigm for medical diagnoses and prognoses prediction. The core mechanism of the proposed method relies on a centroid classification algorithm whose logic is exploited to formulate the classification task as a real-valued optimisation problem. A novel metaheuristic combining the algorithmic structure of Swarm Intelligence optimisers with the probabilistic search models of Estimation of Distribution Algorithms is designed to optimise such a problem, thus leading to high-accuracy predictions. This method is tested over 11 medical datasets and compared against 14 cherry-picked classification algorithms. Results show that the proposed approach is competitive and superior to the state-of-the-art on several occasions

Chronic Healthcare Spending Disease: A Macro Diagnosis and Prognosis

The amount Canadians spend on healthcare is set to rise rapidly over the next two decades and Canadians need to face up to tough choices to deal with this “spending disease.” The study examines the trajectory of total healthcare spending – public and private – in Canada and the policy choices Canadians must make in response. The authors estimate the extent to which healthcare spending is going to absorb a greater fraction of income than Canadians have experienced to date under two scenarios: a baseline scenario drawn from historical experience, and an optimistic scenario, which assumes an unprecedented improvement in the efficiency and effectiveness of the healthcare system and large improvement in potential economic growth. Canadians must choose some combination of: 1) a sharp reduction in public services, other than health care; 2) increased taxes to finance the public share of healthcare spending; 3) increased individual spending on healthcare services currently insured by provinces, through some form of co-payment or through delisting of services that are currently publicly financed; 4) or a degradation of publicly insured healthcare standards – longer queues, and services of poorer quality.The Health Papers, healthcare spending, Canada

An Integrated Framework for Model-Based Distributed Diagnosis and Prognosis

Diagnosis and prognosis are necessary tasks for system reconfiguration and fault-adaptive control in complex systems. Diagnosis consists of detection, isolation and identification of faults, while prognosis consists of prediction of the remaining useful life of systems. This paper presents a novel integrated framework for model-based distributed diagnosis and prognosis, where system decomposition is used to enable the diagnosis and prognosis tasks to be performed in a distributed way. We show how different submodels can be automatically constructed to solve the local diagnosis and prognosis problems. We illustrate our approach using a simulated four-wheeled rover for different fault scenarios. Our experiments show that our approach correctly performs distributed fault diagnosis and prognosis in an efficient and robust manner

Diagnosis and prognosis of slow speed bearing behavior under grease starvation condition

This document is the Accepted Manuscript version. The final, definitive version of this paper has been published in Structural Health Monitoring, April 2017, DOI: https://doi.org/10.1177/1475921717704620, published by SAGE Publishing, All rights reserved.The monitoring and diagnosis of rolling element bearings with acoustic emission and vibration measurements has evolved as one of the much used techniques for condition monitoring and diagnosis of rotating machinery. Furthermore, recent developments indicate the drive toward integration of diagnosis and prognosis algorithms in future integrated machine health management systems. With this in mind, this article is an experimental study of slow speed bearings in a starved lubricated contact. It investigates the influence of grease starvation conditions on detection and monitoring natural defect initiation and propagation using acoustic emission approach. The experiments are also aimed at a comparison of results acquired by acoustic emission and vibration diagnosis on full-scale axial bearing. In addition to this, the article concentrates on the estimation of the remaining useful life for bearings while in operation. To implement this, a multilayer artificial neural network model has been proposed to correlate the selected acoustic emission features with corresponding bearing wear throughout laboratory experiments. Experiments confirm that the obtained results were promising and selecting this appropriate signal processing technique can significantly affect the defect identification.Peer reviewedFinal Accepted Versio

Cortical blindness: Etiology, diagnosis, and prognosis

We examined 15 patients with cortical blindness, reviewed the records of 10 others, and compared these 25 patients to those in previous studies of cortical blindness. Although cerebrovascular disease was the most common cause in our series, surgery, particularly cardiac surgery, and cerebral angiography were also major causes. Only 3 patients denied their blindness, although 4 others were unaware of their visual loss. Electroencephalograms (EEGs) were performed during the period of blindness in 20 patients and all recordings were abnormal, with absent alpha rhythm. Visual evoked potentials recorded during blindness were abnormal in 15 of 19 patients, but did not correlate with the severity of visual loss or with outcome. Bioccipital lucencies were found in computed tomographic (CT) scans of 14 patients; none of the 14 regained good vision. Recovery of vision was poor in all 8 patients who had a spontaneous stroke, but fair or good in 11 of the other 17 patients. Prognosis was best in patients under the age of 40 years, in those without a history of hypertension or diabetes mellitus, and in those without associated cognitive, language, or memory impairments. We conclude that (1) the prognosis in cortical blindness is poor when caused by stroke; (2) EEGs are more useful than visual evoked potentials for diagnosis; and (3) bioccipital abnormalities shown on CT scan are associated with a poor prognosis.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/50318/1/410210207_ftp.pd

Diagnosis and Prognosis of Severe Dengue

Dengue has a broad spectrum of clinical symptoms, ranging from asymptomatic infection, undifferentiated fever and dengue fever (DF) to dengue hemorrhagic fever (DHF) or dengue shock syndrome (DSS). DHF and DSS are the most severe forms of the disease, as they involve bleeding and hypovolemic shock and may lead to death if they are not diagnosed early and treated correctly. Every year, about 36 million cases of DF, of which about 2.1 million cases are DHF/DSS resulting in 21,000 deaths among children and young adults, are reported. Dengue not only has negative effects on public health worldwide but also poses significant economic burden. However, no licensed vaccines or (specific) anti-viral therapies for prevention or treatment of dengue are available. Thus, timely diagnosis and an accurate prognosis of severe dengue in the first few days of illness for clinical triage, treatment management, disease surveillance and research activities are vital and very helpful. We conducted three studies aiming to identify early markers of dengue, especially severe dengue and identify prognostic markers of severe dengue in Vietnamese children with clinically suspected dengue within the first few days of the illness. The results firstly showed that plasma collected within the first week of the illness could be used for dengue diagnosis as well as differentiation between primary and secondary dengue virus infections. Secondly, the research showed that plasma concentration of NS1 correlated with plasma viraemia and associated with DSS. NS1 concentrations in enrolment plasma of patients within the first four days of illness could be used for predicting DSS in patients with DENV-1 or DENV-2 infections. Thirdly, in the first three days of illness, we observed differences in clinical and haematological profiles between patients with DHF and those with DF or other febrile illnesses. Logistic models were then generated using the early clinical characteristics and/or haematological profiles to predict patients who will develop DHF. Our findings also showed that a greater virus burden leads to an augmented cascade of plasma concentrations of IL-1β, IL-2, IL-4, IL-6, IL-10, IL-12p70, IL-13, IFNγ and TNFα in DHF patients compared to DF patients. This thesis shows the results and also points out predictive models that may be used to prognosticate of severe dengue among patients with clinically suspected dengue who are admitted to hospital within the first few days of the illness