Results for 'cardiovascular'

38 found
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  1.  50
    OPTIMIZED CARDIOVASCULAR DISEASE PREDICTION USING MACHINE LEARNING ALGORITHMS.S. Yoheswari - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):350-359.
    Cardiovascular diseases (CVD) represent a significant cause of morbidity and mortality worldwide, necessitating early detection for effective intervention. This research explores the application of machine learning (ML) algorithms in predicting cardiovascular diseases with enhanced accuracy by integrating optimization techniques. By leveraging data-driven approaches, ML models can analyze vast datasets, identifying patterns and risk factors that traditional methods might overlook. This study focuses on implementing various ML algorithms, such as Decision Trees, Random Forest, Support Vector Machines, and Neural Networks, (...)
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  2.  43
    Innovative Approaches in Cardiovascular Disease Prediction Through Machine Learning Optimization.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):350-359.
    Cardiovascular diseases (CVD) represent a significant cause of morbidity and mortality worldwide, necessitating early detection for effective intervention. This research explores the application of machine learning (ML) algorithms in predicting cardiovascular diseases with enhanced accuracy by integrating optimization techniques. By leveraging data-driven approaches, ML models can analyze vast datasets, identifying patterns and risk factors that traditional methods might overlook. This study focuses on implementing various ML algorithms, such as Decision Trees, Random Forest, Support Vector Machines, and Neural Networks, (...)
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  3. Predictive Modeling of Obesity and Cardiovascular Disease Risk: A Random Forest Approach.Mohammed S. Abu Nasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 7 (12):26-38.
    Abstract: This research employs a Random Forest classification model to predict and assess obesity and cardiovascular disease (CVD) risk based on a comprehensive dataset collected from individuals in Mexico, Peru, and Colombia. The dataset comprises 17 attributes, including information on eating habits, physical condition, gender, age, height, and weight. The study focuses on classifying individuals into different health risk categories using machine learning algorithms. Our Random Forest model achieved remarkable performance with an accuracy, F1-score, recall, and precision all reaching (...)
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  4.  32
    Efficient Cloud-Enabled Cardiovascular Disease Risk Prediction and Management through Optimized Machine Learning.P. Selvaprasanth - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):454-475.
    The world's leading cause of morbidity and death is cardiovascular diseases (CVD), which makes early detection essential for successful treatments. This study investigates how optimization techniques can be used with machine learning (ML) algorithms to forecast cardiovascular illnesses more accurately. ML models can evaluate enormous datasets by utilizing data-driven techniques, finding trends and risk factors that conventional methods can miss. In order to increase prediction accuracy, this study focuses on adopting different machine learning algorithms, including Decision Trees, Random (...)
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  5.  35
    Scalable Cloud Solutions for Cardiovascular Disease Risk Management with Optimized Machine Learning Techniques.A. Manoj Prabaharan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):454-470.
    The predictive capacity of the model is evaluated using evaluation measures, such as accuracy, precision, recall, F1-score, and the area under the ROC curve (AUC-ROC). Our findings show that improved machine learning models perform better than conventional methods, offering trustworthy forecasts that can help medical practitioners with early diagnosis and individualized treatment planning. In order to achieve even higher predicted accuracy, the study's conclusion discusses the significance of its findings for clinical practice as well as future improvements that might be (...)
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  6. The Effect of Evoking Nostalgic Memories on the Homeostatic Variables (Mental and Physical) Among Cardiovascular Patients.Hossein Dabbagh - 2018 - Advances in Cognitive Science 19 (4):57-69.
    Nostalgia as one of the complex emotions has been challenged over the past few decades due to its psychological and physiological functions. The present experiment investigates the effect of recalling nostalgic memories on amelioration of homeostatic and health state of people with cardiovascular disease. Method: The participants were 30 patients who were hospitalized for angiography procedure. The research was based on an experimental design with randomized and post-test groups. The instruments used included a thermometer with ° C, a checkout (...)
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  7.  35
    Optimized Cloud Computing Solutions for Cardiovascular Disease Prediction Using Advanced Machine Learning.Kannan K. S. - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):465-480.
    The world's leading cause of morbidity and death is cardiovascular diseases (CVD), which makes early detection essential for successful treatments. This study investigates how optimization techniques can be used with machine learning (ML) algorithms to forecast cardiovascular illnesses more accurately. ML models can evaluate enormous datasets by utilizing data-driven techniques, finding trends and risk factors that conventional methods can miss. In order to increase prediction accuracy, this study focuses on adopting different machine learning algorithms, including Decision Trees, Random (...)
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  8.  28
    Hybrid Cloud-Machine Learning Framework for Efficient Cardiovascular Disease Risk Prediction and Treatment Planning.Kannan K. S. - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):460-480.
    Data preparation, feature engineering, model training, and performance evaluation are all part of the study methodology. To ensure reliable and broadly applicable models, we utilize optimization techniques like Grid Search and Genetic Algorithms to precisely adjust model parameters. Features including age, blood pressure, cholesterol levels, and lifestyle choices are employed as inputs for the machine learning models in the dataset, which consists of patient medical information. The predictive capacity of the model is evaluated using evaluation measures, such as accuracy, precision, (...)
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  9. The Case Fatality Rate in COVID-19 Patients With Cardiovascular Disease: Global Health Challenge and Paradigm in the Current Pandemic.Siddhartha Dan, Mohit Pant & Sushil Kumar Upadhyay - 2021 - Curr Pharmacol Rep 6:1-10.
    Purpose of Review Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is identified from Wuhan, China, and has spread almost worldwide. Recently, the newly identified SARS-CoV-2 has been confirmed to kill millions of people worldwide and is dangerous to society health, survival, and livelihood. The people with cardiovascular problems are noticed as most common patients of coronavirus disease 2019 (COVID-19). There is a greater risk of mortality and morbidity in these patients than other patients of COVID-19. In the heart, expressed angiotensin-converting (...)
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  10.  28
    Cloud-Enabled Risk Management of Cardiovascular Diseases Using Optimized Predictive Machine Learning Models.Kannan K. S. - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):460-475.
    Data preparation, feature engineering, model training, and performance evaluation are all part of the study methodology. To ensure reliable and broadly applicable models, we utilize optimization techniques like Grid Search and Genetic Algorithms to precisely adjust model parameters. Features including age, blood pressure, cholesterol levels, and lifestyle choices are employed as inputs for the machine learning models in the dataset, which consists of patient medical information. The predictive capacity of the model is evaluated using evaluation measures, such as accuracy, precision, (...)
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  11.  37
    Machine Learning-Driven Optimization for Accurate Cardiovascular Disease Prediction.Yoheswari S. - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):350-359.
    The research methodology involves data preprocessing, feature engineering, model training, and performance evaluation. We employ optimization methods such as Genetic Algorithms and Grid Search to fine-tune model parameters, ensuring robust and generalizable models. The dataset used includes patient medical records, with features like age, blood pressure, cholesterol levels, and lifestyle habits serving as inputs for the ML models. Evaluation metrics, including accuracy, precision, recall, F1-score, and the area under the ROC curve (AUC-ROC), assess the model's predictive power.
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  12. Predicting Heart Disease using Neural Networks.Ahmed Muhammad Haider Al-Sharif & Samy S. Abu-Naser - 2023 - International Journal of Academic Information Systems Research (IJAISR) 7 (9):40-46.
    Cardiovascular diseases, including heart disease, pose a significant global health challenge, contributing to a substantial burden on healthcare systems and individuals. Early detection and accurate prediction of heart disease are crucial for timely intervention and improved patient outcomes. This research explores the potential of neural networks in predicting heart disease using a dataset collected from Kaggle, consisting of 1025 samples with 14 distinct features. The study's primary objective is to develop an effective neural network model for binary classification, identifying (...)
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  13. Fair Allocation of GLP-1 and Dual GLP-1-GIP Receptor Agonists.Ezekiel J. Emanuel, Johan L. Dellgren, Matthew S. McCoy & Govind Persad - forthcoming - New England Journal of Medicine.
    Glucagon-like peptide-1 (GLP-1) receptor agonists, such as semaglutide, and dual GLP-1 and glucose-dependent insulinotropic polypeptide (GIP) receptor agonists, such as tirzepatide, have been found to be effective for treating obesity and diabetes, significantly reducing weight and the risk or predicted risk of adverse cardiovascular events. There is a global shortage of these medications that could last several years and raises questions about how limited supplies should be allocated. We propose a fair-allocation framework that enables evaluation of the ethics of (...)
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  14. Individual Climate Risks at the Bounds of Rationality.Avram Hiller - 2023 - In Adriana Placani & Stearns Broadhead (eds.), _Risk and Responsibility in Context_. New York: Routledge. pp. 249-271.
    All ordinary decisions involve some risk. If I go outside for a walk, I may trip and injure myself. But if I don’t go for a walk, I slightly increase my chances of cardiovascular disease. Typically, we disregard most small risks. When, for practical purposes, is it appropriate for one to ignore risk? This issue looms large because many activities performed by those in wealthy societies, such as driving a car, in some way risk contributing to climate harms. Are (...)
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  15. Scary Acute Left Main Coronary Artery Thrombus as an Initial Presentation of a Hereditary Thrombophilia: When to Go Out of Routine?Sinem Kilic, Ahmet Hakan Ates, Uğur Canpolat & Kudret Aytemir - 2023 - European Journal of Therapeutics 29 (2):247-249.
    Patients with either hereditary or acquired thrombophilia can present with arterial and venous thrombotic complications. However, it is unclear to whom the thrombophilia panel should be assessed, particularly in patients presenting with a common cardiovascular risk factor and acute coronary thrombus. Herein, we presented the management of an active smoker female patient who presented to our emergency room with inferior acute ST-segment elevation myocardial infarction, and hereditary thrombophilia has been diagnosed due to the presence of substantial left main coronary (...)
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  16. Prediction Heart Attack using Artificial Neural Networks (ANN).Ibrahim Younis, Mohammed S. Abu Nasser, Mohammed A. Hasaballah & Samy S. Abu-Naser - 2023 - International Journal of Engineering and Information Systems (IJEAIS) 7 (10):36-41.
    Abstract Heart Attack is the Cardiovascular Disease (CVD) which causes the most deaths among CVDs. We collected a dataset from Kaggle website. In this paper, we propose an ANN model for the predicting whether a patient has a heart attack or not that. The dataset set consists of 9 features with 1000 samples. We split the dataset into training, validation, and testing. After training and validating the proposed model, we tested it with testing dataset. The proposed model reached an (...)
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  17. Emotion regulation in psychopathy.Helen Casey, Robert D. Rogers, Tom Burns & Jenny Yiend - 2013 - Biological Psychology 92:541–548.
    Emotion processing is known to be impaired in psychopathy, but less is known about the cognitive mechanisms that drive this. Our study examined experiencing and suppression of emotion processing in psychopathy. Participants, violent offenders with varying levels of psychopathy, viewed positive and negative images under conditions of passive viewing, experiencing and suppressing. Higher scoring psychopathics were more cardiovascularly responsive when processing negative information than positive, possibly reflecting an anomalously rewarding aspect of processing normally unpleasant material. When required to experience emotional (...)
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  18. Are noetic feelings embodied? The case for embodied metacognition.John Dorsch - 2023 - Philosophical Psychology 1:1-23.
    One routinely undergoes a noetic feeling (also called “metacognitive feeling” or “epistemic feeling”), the so-called “feeling of knowing”, whenever trying to recall a person’s name. One feels the name is known despite being unable to recall it. Other experiences also fall under this category, e.g., the tip-of-the-tongue experience, the feeling of confidence. A distinguishing characteristic of noetic feelings is how they are crucially related to the facts we know, so much so that the activation of semantic memory can easily result (...)
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  19. A CLIPS-Based Expert System for Heart Palpitations Diagnosis.Fadi N. Qanoo, Raja E. N. Altarazi & Samy S. Abu-Naser - 2023 - International Journal of Academic Information Systems Research (IJAISR) 7 (6):10-15.
    Heart palpitations, while often benign, can sometimes be indicative of severe underlying conditions requiring immediate intervention. Accurate and swift diagnosis thus remains a clinical priority. "A CLIPS-Based Expert System for Heart Palpitations Diagnosis" represents a novel approach to addressing this challenge, harnessing the power of artificial intelligence and rule-based expert systems. Specifically, this system applies a suite of 7 if-then rules to evaluate potential heart palpitations causes and assign one of three outcomes: 1) A confirmed diagnosis of heart palpitations, 2) (...)
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  20. Factors Influencing College Students' Perception on Participating in Swimming Activities.Louie Gula, Marlon P. Ribon, Allyana Athens Alejandrino & Mario Acero Galeon Jr - 2022 - Partners Universal International Research Journal 1 (2):103-111.
    The purpose of this research is to determine the variables influencing college students' engagement in swimming activities, as well as the significant themes that often appear in these occurrences. A descriptive research design was used to identify the factors influencing college students' perception of participating in swimming activities. Descriptive research is a type of nonexperimental study that aims to describe the features of phenomena as it occurs. It was found out that participating in swimming activities provides various benefits, some of (...)
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  21. Cerebral blood flow autoregulation is impaired in schizophrenia.Hsiao-Lun Ku, Timothy Lane & et al - 2017 - Schizophrenia Research:xx-yy.
    Patients with schizophrenia have a higher risk of cardiovascular diseases and higher mortality from them than does the general population; however, the underlying mechanism remains unclear. Impaired cerebral autoregulation is associated with cerebrovascular diseases and their mortality. Increased or decreased cerebral blood flow in different brain regions has been reported in patients with schizophrenia, which implies impaired cerebral autoregulation. This study investigated the cerebral autoregulation in 21 patients with schizophrenia and 23 age- and sex-matched healthy controls. None of the (...)
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  22. The relationships between democratic experience, adult health, and cause-specific mortality in 170 countries between 1980 and 2016: an observational analysis.Simon Wigley - 2019 - The Lancet 393 (10181):1628-1640.
    Background Previous analyses of democracy and population health have focused on broad measures, such as life expectancy at birth and child and infant mortality, and have shown some contradictory results. We used a panel of data spanning 170 countries to assess the association between democracy and cause-specific mortality and explore the pathways connecting democratic rule to health gains. -/- Methods We extracted cause-specific mortality and HIV-free life expectancy estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (...)
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  23. Physiology of long pranayamic breathing: Neural respiratory elements may provide a mechanism that explains how slow deep breathing shifts the autonomic nervous system.Jerath Ravinder, James W. Edry, Vernon A. Barnes & Vandna Jerath - 2006 - Medical Hypotheses 67 (3):566-571.
    Pranayamic breathing, defined as a manipulation of breath movement, has been shown to contribute to a physiologic response characterized by the presence of decreased oxygen consumption, decreased heart rate, and decreased blood pressure, as well as increased theta wave amplitude in EEG recordings, increased parasympathetic activity accompanied by the experience of alertness and reinvigoration. The mechanism of how pranayamic breathing interacts with the nervous system affecting metabolism and autonomic functions remains to be clearly understood. It is our hypothesis that voluntary (...)
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  24. REVIEW OF MUSIC AND ITS THERAPEUTICS W.S.R. AYURVEDIC CLASSICS (BRIHATRAYEE.Dr Devanand Upadhyay - 2016 - Indian Journal of Agriculture and Allied Sciences 2 (1):114-118.
    Ayurveda is the science of living being. With the aim of health and procurement of disease it almost covers all facets of life. It includes health of an individual at physical, mental, spiritual, social level. Ayurvedic classics includes brihatrayee samhita like Charak, Sushruta and Ashtanga Hridaya. A review based study of music (geet, sangeet) was done in these classics to explore whether these classics includes any form of music as therapy or not. Based on review of these classics it was (...)
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  25. Effects of Moderate Exercise Training On ApoE And ApoCIII In Metabolic Syndrome.Kutluhan Ertekin, Metin Baştuğ & Asena Gökçay Canpolat - 2023 - European Journal of Therapeutics 29 (1):65-73.
    Introduction: Metabolic syndrome (MetS) is an endocrinopathy with a combination of cardiovascular and metabolic compounds. In our study, it is expected to obtain results showing that mortality rate, loss of workforce, and treatment costs due to disorders caused by MetS can be reduced by physical exercise. The study analyses the effect of moderate exercise training on this Apolipoprotein E (ApoE), Apolipoprotein CIII (ApoCIII), adiponectin, resistin, interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) which are thought to have a role in (...)
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  26. Fertilidade em Vacas Leiteiras: Fisiologia e Manejo.Emanuel Isaque Cordeiro da Silva - manuscript
    FERTILIDADE EM VACAS LEITEIRAS: FISIOLOGIA E MANEJO -/- INTRODUÇÃO -/- A fertilidade das vacas com aptidão leiteira tem apresentado queda de quase 1% ao ano nos últimos 30 anos como apresentam os estudos acerca da reprodução de bovinos leiteiros; essa diminuição tem coincidido com um aumento sustentado na produção de leite. Estudos realizados a partir da década de 1960 pelo NRC, demonstraram que nos rebanhos leiteiros da América do Norte, nessa década, era conseguido emprenhar até 65% das vacas inseminadas, enquanto, (...)
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  27. COVID-19 Pandemic: Evidences from Clinical Studies.Ravi Shankar Singh, Abhishek Kumar Singh, Kamla Kant Shukla & Amit Kumar Tripathi - 2020 - Journal of Community and Public Health Nursing 6 (4):251.
    The public health crisis is started with emergence of new coronavirus on 11 February 2020 which triggered as coronavirus disease-2019 (COVID-19) pandemics. The causative agent in COVID-19 is made up of positively wrapped single-stranded RNA viruses ~ 30 kb in size. The epidemiology, clinical features, pathophysiology, and mode of transmission have been documented well in many studies, with additional clinical trials are running for several antiviral agents. The spreading potential of COVID-19 is faster than its two previous families, the severe (...)
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  28. Covid-19 Second Wave: Challenges for Education and Disaster Management.V. P. Singh & Prabhakar Singh - 2021 - In Verma (ed.), COVID-19 SECOND WAVE: CHALLENGES FOR SUSTAINABLE DEVELOPMENT. Prayagraj: ABRF. pp. 130-132.
    Coronavirus disease (Covid-19) is an infectious disease caused by the SARS-CoV-2 virus. Spreading rate of mutated corona virus (delta variant) during second wave was very fast. Most of the people infected with the COVID-19 virus experienced mild to moderate to severe respiratory illness. Although patients in the second wave were younger but the duration of hospitalization and case fatality rate were lower than those in the first wave. During first wave of Covid-19 it was observed that persons above 55 years (...)
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  29. Enhancing Reduced Risk of Obese Patient Exposure to COVID-19 Attack through Food and Nutritional Adjustment.Patience Abosede Olunusi & Motunrayo Risikat Asunmo - 2023 - International Journal of Home Economics, Hospitality and Allied Research 2 (2):206-218.
    The COVID-19 pandemic is a major global challenge. There are several risk factors associated with mortality in patients with COVID-19, including age, gender, diabetes mellitus, cerebrovascular, cardiovascular, and pulmonary diseases. Among these factors, patients with cardiovascular disease, diabetes mellitus, and obesity have the highest mortality rates. This paper aims to review how adjusting food and nutrition can help reduce the risk of obese patients contracting COVID-19. Various literature sources were examined, including studies on the genetics of obesity and (...)
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  30. Covid 19 pandemic: Impact on masses and prevention knowhow. Namita, Chitra Singh & Vivek Kumar - 2020 - International Journal of Medical and Health Research 6 (9):6-9.
    Today the whole world is facing a very difficult time due to corona virus which initially originated in Wuhan city of China. In China an unusual pneumonia was noticed earlier which later recognized as a pandemic. There have been two events in the past wherein crossover of animal corona viruses to humans has resulted in severe disease, one was SARS-CoV and the other was MERS-CoV. The genetic sequence of the COVID19 showed more than 80% similarities to SARS-CoV and 50% to (...)
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  31. DISCOURSE ON NON-COMMUNICABLE DISEASES INTERVENTIONS IN GHANA (1990-2018).Samuel Adu-Gyamfi, Lucky Tomdi & Kwasi Amakye-Boateng - 2020 - Journal of Basic and Applied Research International 26 (2):17-26.
    Non-communicable diseases (NCDs) such as cardiovascular diseases and diabetes are reported to have caused significant deaths for more than a decade. Consequently, NCDs have posed as a threat to the socio-economic well-being of individuals and families, contributed to a rise in healthcare costs and largely undermined the attainment of the Sustainable Development Goals (SDGs) especially in developing countries. According to the World Health Organization (WHO), the prevalence of NCDs have compounded the problem of already ill equipped healthcare systems in (...)
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  32. The Role of Vitamin D in the Incidence of Metabolic Syndrome in Undergraduate Female Students in Saudi Arabia.aHala M. Abdelkarem, Aishah H. Alamri, bFadia Y. Abdel Megeid, cMervat M. Al-Sayed & Omyma K. Radwan - 2018 - International Journal of Academic Health and Medical Research (IJAHMR) 2 (11):7-12.
    Abstract: Background: Vitamin D insufficiency/deficiency prevalent in all age groups across the world is common in obesity and may play an important role in the risk factors of metabolic syndrome (MS). Objectives: This cross-sectional study is to evaluate the relationship between levels of adiponectin and circulating 25(OH)D, and its effect on metabolic biomarker among overweight/obese female students. Methods: Three hundred female students; with mean age 20.9 ± 3.2 years were attending the Aljouf University, Sakaka, Saudi Arabia. They were randomly selected (...)
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  33. Evolutionary Study of Chronic Non-Communicable Diseases Policy as Healthcare Intervention in Ghana (2000-2019).Samuel Adu-Gyamfi, Lucky Tomdi, Michael Nimoh & Benjamin Darkwa Dompreh - 2020 - International Journal of Body, Mind and Culture 6 (4):185-200.
    The incidence of chronic non-communicable diseases (NCDs) such as diabetes, hypertension, cancers and cardiovascular diseases in Ghana has created a new mix of healthcare challenge for the country.
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  34. Ethical considerations of medical cannabis prescription.Cole Zachary - manuscript
    Despite analgesic and emetogenic benefits, cannabis has been banned from prescription in a number of western countries. Although some benefits are shared by drugs already available, the options of prescription are limited to the physician. The negative side-effects of cannabis do not justify this limitation on freedom and autonomy. Recreational use warrants limitations, as the search for euphoria is regularly believed to be a non-autonomous behavior. Medical prescriptions serve an analgesic and emetogenic purpose comparable to other prescribed drugs. This vindicates (...)
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  35. Somatic aphasia: Mismatch of body sensations with autonomic stress reactivity in psychopathy.Yu Gao, Adrian Raine & Robert A. Schug - 2012 - Biological Psychology 90:228–233.
    Background— Although one of the main characteristics of psychopaths is a deficit in emotion, it is unknown whether they show a fundamental impairment in appropriately recognizing their own body sensations during an emotion-inducing task. Method— Skin conductance and heart rate were recorded in 138 males during a social stressor together with subjective reports of body sensations. Psychopathic traits were assessed using the Psychopathy Checklist – Revised (PCL-R) 2nd edition (Hare, 2003). Results— Nonpsychopathic controls who reported higher body sensations showed higher (...)
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  36. Emotional regulation and depression: A potential mediator between heart and mind.Angelo Compare, Cristina Zarbo, Edo Shonin, William Van Gordon & Chiara Marconi - 2014 - Cardiovascular Psychiatry and Neurology 2014:ID 324374, 10 pages.
    A narrative review of the major evidence concerning the relationship between emotional regulation and depression was conducted. The literature demonstrates a mediating role of emotional regulation in the development of depression and physical illness. Literature suggests in fact that the employment of adaptive emotional regulation strategies (e.g., reappraisal) causes a reduction of stress-elicited emotions leading to physical disorders. Conversely, dysfunctional emotional regulation strategies and, in particular, rumination and emotion suppression appear to be influential in the pathogenesis of depression and physiological (...)
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  37. Translating Trial Results in Clinical Practice: the Risk GP Model.Jonathan Fuller & Luis J. Flores - 2016 - Journal of Cardiovascular Translational Research 9:167-168.
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  38. Aortic Stenosis and Stressed Heart Morphology.Celalettin Karatepe - 2014 - World Journal of Cardiovascular Surgery 4:151-157.
    Myocardial geometric remodeling is a response to increased stress which includes increased afterload situations during clinical conditions. In this review, we have focused on early and late geometric features in aortic stenosis, importance of recognition of these findings and consequences due to progression of valve disease. We have also pointed out the similarities in early focal and global myocardial geometric remodeling in acute and chronic conditions as hypertension and acute stress cardiomypathy which are associated with myocardial functional and geometric response (...)
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