Machine learning models for Parkinson’s disease detection and stage classification based on spatial-temporal gait parameters

BackgroundParkinson’s disease (PD) is a chronic and progressive neurodegenerative disease with no cure, presenting a challenging diagnosis and management. However, despite a significant number of criteria and guidelines have been proposed to improve the diagnosis of PD and to determine the PD stage, the gold standard for diagnosis and symptoms monitoring of PD is still mainly based on clinical evaluation, which includes several subjective factors. The use of machine learning (ML) algorithms in spatial-temporal gait parameters is an interesting advance with easy interpretation and objective factors that may assist in PD diagnostic and follow up.Research questionThis article studies ML algorithms for: i) distinguish people with PD vs. matched-healthy individuals; and ii) to discriminate PD stages, based on selected spatial-temporal parameters, including variability and asymmetry.MethodsGait data acquired from 63 people with PD with different levels of PD motor symptoms severity, and 63 matched-control group individuals, during self-selected walking speed, was study in the experiments.ResultsIn the PD diagnosis, a classification accuracy of 84.6 %, with a precision of 0.923 and a recall of 0.800, was achieved by the Naïve Bayes algorithm. We found four significant gait features in PD diagnosis: step length, velocity and width, and step width variability. As to the PD stage identification, the Random Forest outperformed the other studied ML algorithms, by reaching an Area Under the ROC curve of 0.786. We found two relevant gait features in identifying the PD stage: stride width variability and step double support time variability.SignificanceThe results showed that the studied ML algorithms have potential both to PD diagnosis and stage identification by analysing gait parameters.     

Interpersonal positive reframing in the daily lives of couples coping with breast cancer

Abstract

Objectives: This study examined word use as an indicator of interpersonal positive reframing in daily conversations of couples coping with breast cancer and as a predictor of stress.

Design: The Electronically Activated Recorder (EAR) and Linguistic Inquiry and Word Count (LIWC) were used to examine naturally occurring word use conceptually linked to positive reframing (positive emotion, negative emotion, and cognitive processing words).

Sample: Fifty-two couples coping with breast cancer.

Methods: Couples wore the EAR, a device participants wear, that audio-recorded over one weekend (>16,000 sound files), and completed self-reports of positive reframing (COPE) and stress (Perceived Stress Scale). LIWC, a software program, measured word use.

Findings: Both partners’ word use (i.e., positive emotion and cognitive processing words) was associated with their own reported positive reframing, and spouses’ word use was also indicative of patients’ positive reframing. Results also revealed that, in general, words indicating positive reframing predicted lower levels of stress.

Conclusions: Findings supported the hypothesis that partners—and particularly spouses of breast cancer patients—may assist each other’s coping by positively reframing the cancer experience and other negative experiences in conversation.     

The Relationship between College Graduate’s Dual Self-Consciousness and Job Search Clarity: The Mediating Role of Perceived Stress

The aim of the study was to explore the relationship between college graduates’ dual self-consciousness, job search clarity and perceived stress, and reveal the mediating role of perceived stress between dual self-consciousness and job search clarity. In this study, 467 college graduates were investigated using the Dual Self-Consciousness Scale, Job Search Clarity Scale, and Perceived Stress Scale. After controlling for gender, age, and region, the results revealed that: (1) private self-consciousness has a significant positive predictive effect on job search clarity; (2) perceived stress has a significant negative predictive effect on job search clarity; (3) perceived stress plays partial mediation effects between private self-consciousness and job search clarity; (4) perceived stress plays complete mediation effects between public self-consciousness and job search clarity; (5) perceived stress has suppressing effects between public self-consciousness and job search clarity.     

Robust rigid registration of retinal angiograms through optimization

Retinal fundus photographs are employed as standard diagnostic tools in ophthalmology. Serial photographs of the flow of fluorescein and indocyanine green (ICG) dye are used to determine the areas of the retinal lesions. For objective measurements of features, the registration of the images is a necessity. In this paper, we employ optimization techniques for registration with the help of 2-parameter translational motion model of retinal angiograms, based on non-linear pre-processing (Wiener filtering and morphological gradient) and computation of the similarity criteria for the alignment of the two gradient images for any given rigid transformation. The optimization methods are effectively employed to minimize the similarity criterion.

The presence of noise, the variations in the background and the temporal variation of the fluorescence level pose serious problems in obtaining a robust registration of the retinal images. Moreover, local search strategies are not robust in the case of ICG angiograms, even if one uses a multiresolution approach.

The present work makes a systematic comparison of different optimization techniques, namely the minimization method derived from the optical flow formulation, the Nelder-Mead local search and the HCIAC ant colony metaheuristic, each optimizing a similarity criterion for the gradient images. The impact of the resolution and median filtering of gradient image is studied and the robustness of the approaches is tested through experimental studies, performed on macular fluorescein and ICG angiographies.

Our proposed optimization techniques have shown interesting results especially for high resolution difficult registration problems. Moreover, this approach seems promising for affine (6-parameter motion model) or elastical registrations.     

医院检验科设备的维修分析

医院检验科设备是为临床提供诊断依据最基础也是最常用的检验手段之一，本文简要介绍了检验科设备在日常工作中容易发生的故障判别及修复时的要点。     

英文医学科技论文写作中词的选择与搭配

作者结合实际工作经验简要论述了英文医学科技论文写作中词的选择与搭配的问题,并就如何提高英文写作水平提出了几点建议。     

生物素－链霉亲和素系统在检测HBeAg中的比较

应用链霉亲和素和生物素系统发展成的酶连接免疫吸附测定（ＥＬＩＳＡ）改良法检测ＨＢｅＡｇ，取得较满意效果。标记链霉亲和素－辣根过氧化物酶（ＳＡ－ＨＲＰ）时，两者的重量比以（０．５～０．８）：１为佳，浓度以７μｇ／ｍｌ为最理想；ＳＡ－ＨＲＰ的反应时间以３０ｍｉｎ为适宜。本改良法与生物素亲和素ＥＬＩＳＡ（ＢＡ）法、普通ＥＬＩＳＡ法检测ＨＢｅＡｇ的灵敏度比较，其相对灵敏度高于后二者；用Ａｂｂｏｔｔ试剂作为标准，检测ＨＢｅＡｇ１００人份，其阳性率高于ＢＡ法和普通ＥＬＩＳＡ法。提示链霉亲和素ＥＩ，ＩＳＡ（ＢＳＡ）法可提高方法的特异性及灵敏度。     

淋巴细胞β受体与放射配基结合所需孵育时间的确定

介绍理论运算和实验测量相结合，确定淋巴细胞膜碎片β受体与标记配基结合所需平衡时间的方法。结果表明：二种方法所得平衡时间基本一致。多点法时平衡时间需25-30min；单点法时需5-7min。     

^60Co消毒与高温高压消毒胚胎骨的实验研究

在12只健康家兔下颌骨体部的两侧各造成0.7cm×0.5cm×0.3cm的骨缺损区，分别置入^60Co消毒的胚胎骨和高温高压消毒的胚胎骨，发现高温高压消毒可以替代^60Co消毒胚胎骨进行移植，为临床提供了一种新的用作同种异体移植胚胎骨的消毒方法。