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Risk Factors Categorizations of Ischemic Heart Disease in South-Western Bangladesh

Data Intelligence 2024年第3期6卷 834-868页

作者： M.Raihan Sami Azam Laboni Akter Md.Mehedi Hassan Ryana Quadir Asif Karim saikat mondal Arun More Department of Computer Science and Engineering North Western UniversityKhulna 9100Bangladesh Faculty of Science and Technology Charles Darwin UniversityNT 0909Australia Departmentof Biomedical Engineering Khulna University of Engineering&TechnologyKhulnaBangladeh Computer Science and Engineering Discipline Khulna UniversityKhulna 9208Bangladesh Department of Computer Science and Engineering Daffodil International University(DIU)Bangladesh Department of Cardiology Ter Institute of Rural Health and ResearchMurud-413510India

Ischemic heart disease(IHD)is one of the leading causes of death ***,different geographic regions show different variations of the risk factors of this disease based on the different lifestyles of *** study examines the current IHD condition in southern Bangladesh,a Southeast Asian middle-income *** main approach to this research is an Al-based proposal of a reduced set of the greatest impact clinical traits that may cause *** approach attempts to reduce IHD morbidity and mortality by early detection of risk factors using the reduced set of clinical ***,diagnostic,and symptomatic features were considered for analysing this clinical *** pre-processing utilizes several machine learning techniques to select significant features and make meaningful interpretations.A proposed voting mechanism ranked the selected 138 features by their impact *** this regard,diverse patterns in correlations with variables,including age,sex,career,family history,obesity,etc.,were calculated and explained in terms of voting *** the 138 risk factors,three labels were categorized:high-risk,medium-risk,and low-risk features;19 features were regarded as high,25 were medium,and 94 were considered low impactful *** research's technological methodology and practical goals provide an innovative and resilient framework for addressing IHD,especially in less developed cities and townships of Bangladesh,where the general population's socioeconomic conditions are often *** data collection,pre-processing,and use of this study's complete and comprehensive IHD patient dataset is another innovative *** believe that other relevant research initiatives will benefit from this work.

关键词： Ischemic heart disease Machine learning CVD Data categorization Medical data

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Predictors of severity and outcome and roles of intravenous thrombolysis and biomarkers in first ischemic stroke

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Neuroimmunology and Neuroinflammation 2018年第9期5卷 24-34页

作者： Kartick Chandra Ghosh Ramesh Bhattacharya saikat Ghosh Manoj Mahata Sarbajit Das Suman Das Gourango Prosad mondal Department of Neurology Calcutta National Medical CollegeKolkata PIN-700014India

Aim: Stroke is one of the leading causes of death and disability. The proportion of patients receiving recombinant tissue plasminogen activator is low in our country. Biomarkers to identify patients at risk of severe disease, and guide treatment and prognosis would be valuable. This article aims to identify the factors that can independently prognosticate the acute phase of ischemic stroke. Methods: All patients with the first episode of ischemic stroke admitted to the Neurology Department between 1st December 2017 to 31st March 2018 were included in this pilot study. Stroke severity was evaluated using the National Institute of Health Stroke Scale (NIHSS). Patients being admitted within 4.5 h of onset of symptoms were thrombolysed with injection alteplase. For each patient, 4 serum biomarkers (D-dimer, fibrinogen, C-reactive pro-tein and neuron specific enolase) were evaluated at admission and 24 h later. Discharged patients were assessed on an outpatient basis using the modified Rankin scale. The study primarily aimed to identify the factors predicting the severity and outcome of stroke, and to evaluate the effect of thrombolysis on the outcome. The secondary aim was to evaluate the role of biomarkers to predict the unfavorable outcome and the chance of post thrombolysis hemor-rhage. Results: Out of 30 patients included in the study, 10 had NIHSS 0-4, 12 had NIHSS 5-15 and 8 had NIHSS 16-42. Sixteen patients had unfavorable outcome (mRS score ≥ 2), and 5 patients expired. Old age, history of diabetes, CHADS2 score ≥ 2, and total anterior circulation stroke (TACS) independently affected stroke severity, whereas lowejection fraction < 35%, and TACS, independently predicted unfavorable outcome and mortality. High mean arte-rial blood pressure (MABP) and capillary blood glucose (CBG) at admission were significant predictors of stroke severity, unfavorable outcome, and mortality. Out of 10 thrombolysed patients, two had mRS score ≥ 2 and 3 had the post-thrombolysis hem

关键词： First-ever ischemic stroke thrombolysis biomarkers total anterior circulation stroke fibrinogen

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