Cooperative-Competitive Healthcare Service Negotiation

Service negotiation is a complex activity, especially in complex domains such as healthcare. The provision of healthcare services typically involves the coordination of several professionals with different skills and locations. There is usually negotiation between health- care service providers as different services have specific constraints, variables, and features (scheduling, waiting lists, availability of resources, etc.), which may conflict with each other. While automating the negotiation processes by using software can improve the e±ciency and quality of healthcare services, most of the existing negotiation automations are positional bargaining in nature, and are not suitable for complex scenarios in healthcare services. This paper proposes a cooperative-competitive negotiation model that enables negotiating parties to share their knowledge and work toward optimal solutions. In this model, patients and healthcare providers work together to develop a patient-centered treatment plan. We further automate the new negotiation model with software agents

Pattern identification of biomedical images with time series: contrasting THz pulse imaging with DCE-MRIs

Objective We provide a survey of recent advances in biomedical image analysis and classification from emergent imaging modalities such as terahertz (THz) pulse imaging (TPI) and dynamic contrast-enhanced magnetic resonance images (DCE-MRIs) and identification of their underlining commonalities. Methods Both time and frequency domain signal pre-processing techniques are considered: noise removal, spectral analysis, principal component analysis (PCA) and wavelet transforms. Feature extraction and classification methods based on feature vectors using the above processing techniques are reviewed. A tensorial signal processing de-noising framework suitable for spatiotemporal association between features in MRI is also discussed. Validation Examples where the proposed methodologies have been successful in classifying TPIs and DCE-MRIs are discussed. Results Identifying commonalities in the structure of such heterogeneous datasets potentially leads to a unified multi-channel signal processing framework for biomedical image analysis. Conclusion The proposed complex valued classification methodology enables fusion of entire datasets from a sequence of spatial images taken at different time stamps; this is of interest from the viewpoint of inferring disease proliferation. The approach is also of interest for other emergent multi-channel biomedical imaging modalities and of relevance across the biomedical signal processing community

Investigation of social behaviour patterns using location-based data - a Melbourne case study

Location-based social networks such as Swarm provide a rich source of information on human behaviour and urban functions. Our analysis of data created by users who voluntarily used check-ins with a mobile application can give insight into a user's mobility and behaviour patterns. In this study, we used location-sharing data from Swarm to explore spatiotemporal, geo-temporal and behaviour patterns within the city of Melbourne. Moreover, we used several tools for different datasets. We used the MeaningCloud tool for sentiment analysis and the LIWC15 tool for psychometric analysis. Also, we employed SPSS software for the descriptive statistical analysis on check-in data to reveal meaningful trends and attain a deeper understanding of human behaviour patterns in the city. The results show that most people do not express strong negative or positive emotions in relation to the places they visit. Behaviour patterns vary based on gender. Furthermore, mobility patterns are different on different days of the week as well as at different times of a day but are not necessarily influenced by the weather

Effects of Post-Surgical Parenteral Nutrition on Patients with Gastric Cancer

Background/Aims: In this study, we investigated the effect of post-surgical parenteral nutrition on patients with gastric cancer (GC) and its possible mechanism. Methods: A total of 108 patients were invited to assess for eligibility and 28 patients were excluded. The eighty patients were randomized to either a study group (1 L peripheral intravenous nutrition, 700 kcal) or a control group (1 L isotonic electrolyte solution). Parenteral nutrition was started on day 1 post-surgery and maintained for 4-8 days. Levels of albumin (ALB), prealbumin (PAB), hemoglobin (Hb) were measured before and after treatment. Self-rating Scale of Life Quality (SSLQ) and Quality of life (QoL) was assessed to analyze the patients’ quality of life. Psychological status was evaluated using both the Hospital Anxiety and Depression Scale (HADS-A/D) and the Patient Health Questionnaire-9 (PHQ-9). Immune function was evaluated by flow cytometric analysis of the levels of CD3+, CD4+, and CD8+ cells. Results: Following post-surgical parenteral nutrition, the levels of ALB, PAB and Hb were significantly higher in the study group than those in the control group. QoL and SSLQ scores were also significantly increased, while HAD-A/D and PHQ-9 scores were significantly reduced. Furthermore, the percentages of CD3+ and CD4+ cells, but not CD8+ cells, as well as the CD4+/CD8+ ratio were significantly increased in the study group. There were no significant differences in these parameters between the control and study group prior to surgery. Conclusion: The results suggest that post-surgical parenteral nutrition can significantly improve the nutritional and psychological status, QoL, and immune function of patients treated surgically for GC

A clinical study of the effects of lead poisoning on the intelligence and neurobehavioral abilities of children

BACKGROUND: Lead is a heavy metal and important environmental toxicant and nerve poison that can destruction many functions of the nervous system. Lead poisoning is a medical condition caused by increased levels of lead in the body. Lead interferes with a variety of body processes and is toxic to many organs and issues, including the central nervous system. It interferes with the development of the nervous system, and is therefore particularly toxic to children, causing potentially permanent neural and cognitive impairments. In this study, we investigated the relationship between lead poisoning and the intellectual and neurobehavioral capabilities of children. METHODS: The background characteristics of the research subjects were collected by questionnaire survey. Blood lead levels were detected by differential potentiometric stripping analysis (DPSA). Intelligence was assessed using the Gesell Developmental Scale. The Achenbach Child Behavior Checklist (CBCL) was used to evaluate each child’s behavior. RESULTS: Blood lead levels were significantly negatively correlated with the developmental quotients of adaptive behavior, gross motor performance, fine motor performance, language development, and individual social behavior (P < 0.01). Compared with healthy children, more children with lead poisoning had abnormal behaviors, especially social withdrawal, depression, and atypical body movements, aggressions and destruction. CONCLUSION: Lead poisoning has adverse effects on the behavior and mental development of 2–4-year-old children, prescribing positive and effective precautionary measures

Perceptions of Hierarchical Medical System and Associated Factors in Key Primary Care Practitioners

BackgroundThe establishment and improvement of hierarchical medical system will help optimize health resource allocation and develop a sound healthcare-seeking pattern. As the key practitioners of hierarchical medical system, primary care workers&apos; perception of the system is vital to the implementation of the system, so studying their perception of the system and associated factors is of great significance.ObjectiveTo analyze primary care professionals&apos; perceptions of hierarchical medical system and associated factors based on the results of 2018 Sixth China National Health Survey, providing a reference for further improvement of the system.MethodsFrom April to October 2019, one representative urban district and one suburban county were chosen from each of six selected provinces in which hierarchical medical system has been implemented. Then by stratified random sampling, about six community health centers/township health centers were extracted from each district (county) (46 community health centers and 30 township health centers in total) , in which primary care professionals who were on duty on the day of survey were invited to attend a questionnaire survey for understanding their demographics, perceptions of the importance and effectiveness of, as well as barriers to the implementation of hierarchical medical system.ResultsAltogether, 1 308 cases who effectively completed the survey were included for final analysis. According to the analysis, the benefits of implementing hierarchical medical system were: improving the health service system〔approved by 1 231 cases (94.11%) 〕, improving the healthcare services for patients and residents〔agreed by 1 219 cases (93.20%) 〕; improving the quality of medical services〔1 209 (92.43%) 〕; improving the efficiency of medical services〔1 189 (90.90%) 〕; improving doctor-patient relationship〔1 087 (83.10%) 〕; reducing the medical risk〔786 (60.09%) 〕; reducing medical expenses〔611 (46.71%) 〕. As for the outcome of implementing hierarchical medical system, its implementation would not hinder the development of health institutions〔982 (75.08%) 〕. When it comes to the barriers to the implementation of hierarchical medical system, there were no relevant incentives〔759 (58.03%) 〕, patients and their families&apos; were unwilling to accept hierarchical medical system due to getting used to free healthcare-seeking pattern〔753 (57.57%) 〕, there were no unified bi-directional referral criteria and system〔712 (54.43%) 〕, the implementation of hierarchical medical system may lead to conflict of interests between medical institutions〔451 (34.48%) 〕, there was no an effective referral route〔403 (30.81%) 〕, their medical institutions had insufficient capacities to effectively implement hierarchical medical system〔387 (29.59%) 〕. Univariate analysis revealed that primary care professionals&apos; perceptions of hierarchical medical system differed significantly by province, sex, educational background, professional title, type of their medical institution, and type of post (P&lt;0.05) . Multiple linear regression analysis indicated that province, sex, educational background, professional title, and officially budgeted post were associated with primary care professionals&apos; perceptions of hierarchical medical system (P&lt;0.05) .ConclusionThese primary care professionals had good perceptions of the importance and effectiveness of the implementation of hierarchical medical system, but also showed their concerns about the barriers to its implementation. Professional title and province were associated with their perceptions of the system. To promote the implementation of hierarchical medical system, it is suggested that the government departments increase investment, improve policy details, provide corresponding incentives, and carry out targeted publicity and education

The role of 245 phase in alkaline iron selenide superconductors revealed by high pressure studies

Here we show that a pressure of about 8 GPa suppresses both the vacancy order and the insulating phase, and a further increase of the pressure to about 18 GPa induces a second transition or crossover. No superconductivity has been found in compressed insulating 245 phase. The metallic phase in the intermediate pressure range has a distinct behavior in the transport property, which is also observed in the superconducting sample. We interpret this intermediate metal as an orbital selective Mott phase (OSMP). Our results suggest that the OSMP provides the physical pathway connecting the insulating and superconducting phases of these iron selenide materials.Comment: 32 pages, 4 figure

Antisocial behavior identification from Twitter feeds using traditional machine learning algorithms and deep learning

Antisocial behavior (ASB) is one of the ten personality disorders included in ‘The Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and falls in the same cluster as Borderline Personality Disorder, Histrionic Personality Disorder, and Narcissistic Personality Disorder. It is a prevalent pattern of disregard for and violation of the rights of others. Online antisocial behavior is a social problem and a public health threat. An act of ASB might be fun for a perpetrator; however, it can drive a victim into depression, self-confinement, low self-esteem, anxiety, anger, and suicidal ideation. Online platforms such as Twitter and Reddit can sometimes become breeding grounds for such behavior by allowing people suffering from ASB disorder to manifest their behavior online freely. In this paper, we propose a proactive approach based on natural language processing and deep learning that can enable online platforms to actively look for the signs of antisocial behavior and intervene before it gets out of control. By actively searching for such behavior, social media sites can prevent dire situations leading to someone committing suicide