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.     

A mechanism for gratitude development in a child

Most scholars consider gratitude as a moral emotion, with only few seeing it as a character trait. As a result, no systematic mechanism has ever been attempted to develop gratitude in children. Given the social issue of widespread lack of gratitude in the one-child generations of China, this article attempts to outline a mechanism of parental moral education for gratitude development. The mechanism is underpinned by love, induction and discipline; and theoretically justified in accordance with key psychological and sociological theories, such as Piaget's theory of moral development, Kohlberg's moral stages theory, attachment theory, Hoffman's internalisation theory, Rest's social justice theory and Baumrind's parenting styles theory. The benefits and potential risks of each strategy of the mechanism are addressed.     

自律:在医患关系中的定位

医疗行为的特殊性，决定了医患双方在医学信息方面的不对称性和医者拥有一定的自由裁量权，因此，医者作为医疗服务的主体，如何增强自律意识，直接关系到诚信的树立及和谐的互动式医患关系的建立和发展。     

加强学科建设提高中医儿科教学质量

中医儿科是河南省重点学科,加强学科管理,健全各项管理规章制度,科学合理设置儿科课程,实现理论与实践的结合,课堂与临床见习的结合;提高教师人文素质、教学水平,是保证儿科教学质量的关键.     

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。     

多种措施并举,加强学风建设

多种措施并举,加强学风建设,包括以师德师风促学风建设、健全教育管理制度、构建具有自身特色的学生工作机制、建立行之有效的激励机制、实施本科生导师制和学导制、丰富教育形式、严肃考风考纪、积极开展课外科技文化活动等,获效显著:学生学习风气良好,自觉遵守校规校纪;学习气氛浓厚,学习成绩提高;涌现出了一大批先进集体和先进个人;优秀大学生先进群体引起社会各界强烈反响;创新与实践能力得到提升.     

中医基础科学人才培养模式的探索

作为国家理科基础，我们中医基础学科从以下4方面做了有益探索：①人才培养注重夯实人文底蕴、坚持中医特色、打造厚实基础、培养创新能力；②教学理念更新；③实践教学强化实验创新、人文社会实践、临床实习、毕业实习、课外科技活动：④改革培养模式。     

方剂学科发展思路与方法

方剂学科传统模式已发生重大变化，现代方剂学以计算机和实验为重要研究手段，熔理论方剂学、实验方剂学及临床方剂学于一炉。现代方剂学科模式的建立必将培育出新的知识增长点，丰富学科内涵，促进研究方向和专业课程的调整，提高学术水平和人才培养质量，实现新世纪方剂学科发展质的飞跃。     

Cocaine tolerance: Interactions among random-ratio and random-interval reinforcement-schedule parameters and repeated exposure to cocaine

Food-deprived pigeons were trained to peck a key under either a three-component multiple random-ratio 5, random-ratio 25, random-ratio 125 schedule or a three-component multiple random-interval 10-sec, random-interval 30-sec, random-interval 125-sec schedule of food presentation. Following determination of acute effects of cocaine (1.0-13.0 mg/kg), are-sponse-rate-reducing dose was given before each daily session. Once performance under conditions of daily administration had become stable, other doses occasionally were substituted for the usual daily dose so that dose effects could be assessed. Tolerance, i.e., a rightward shift in the dose-effect curve was observed in all subjects. For subjects studied under the random-ratio schedules, however, the robustness of the tolerance usually was related to the schedule-parameter value; tolerance was great at lower random values. By contrast, subjects whose responding was maintained by random-interval schedules were less likely to show tolerance that was schedule-parameter dependent. The results also provide suggestive evidence that dose may be an important factor in determining effects of repeated cocaine exposure; repeated administration of larger doses may be less likely to result in tolerance than similar exposure to smaller doses.