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COPDVD: Automated classification of chronic obstructive pulmonary disease on a new collected and evaluated voice dataset

Abstract Background: Chronic obstructive pulmonary disease (COPD) is a severe condition affectingmillions worldwide, leading to numerous annual deaths. The absence of significant symptomsin its early stages promotes high underdiagnosis rates for the affected people. Besidespulmonary function failure, another harmful problem of COPD is the systemic effects,e.g., heart failure or voice distortion. However, the systemic effects […]

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The use of a digital life story to support person-centred care of older adults with dementia: A scoping review

Abstract Introduction: A life story (LS) is a tool healthcare professionals (HCPs) use to help older adults with dementia preserve their identities by sharing their stories. Applied health technology can be considered a niche within welfare technology. Combining technology and nursing, such as using life stories in digital form, may support person-centred care and allow […]

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Relative’s suggestions for improvements in support from health professionals before and after a patient’s death in general palliative care at home: A qualitative register study

Abstract Introduction: The efforts of relatives in providing palliative care (PC) at home areimportant. Relatives take great responsibility, face many challenges and are at increasedrisk of poor physical and mental health. Support for these relatives is important,but they often do not receive the support they need. When PC is provided athome, the support for relatives […]

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Empowering Dementia Diagnosis: A Machine Learning-Driven Automated System

Abstract: Dementia, a neurodegenerative disease, significantly impairs cognitive abilities and is often not diagnosed until the later stages of disease progression. This delayed diagnosis results in missed early intervention, support opportunities and difficulty implementing appropriate care strategies. To address this problem, researchers have proposed automated diagnostic systems that utilize machine learning methods using electronic health […]

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Support given by health professionals before and after a patient’s death to relatives involved in general palliative care at home in Sweden: Findings from the Swedish Register of Palliative Care

Abstract Objectives. General palliative care (PC) is provided more at home, leading to increasedinvolvement of relatives. Although support for relatives is a fundamental component of PC,there are deficiencies in the support provided to relatives when general PC is provided at home.This study aimed to describe the support provided by health professionals before and after apatient’s […]

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Applied Machine Learning Techniques to Diagnose Voice-Affecting Conditions and Disorders: Systematic Literature Review

Abstract Background:Normal voice production depends on the synchronized cooperation of multiple physiological systems, which makes the voice sensitive to changes. Any systematic, neurological, and aerodigestive distortion is prone to affect voice production through reduced cognitive, pulmonary, and muscular functionality. This sensitivity inspired using voice as a biomarker to examine disorders that affect the voice. Technological […]

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Decision Support System for Predicting Mortality in Cardiac Patients Based on Machine Learning

Abstract : Researchers have proposed several automated diagnostic systems based on machine learning and data mining techniques to predict heart failure. However, researchers have not paid close attention to predicting cardiac patient mortality. We developed a clinical decision support system for predicting mortality in cardiac patients to address this problem. The dataset collected for the experimental […]

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Early Prediction of Dementia Using Feature Extraction Battery (FEB) and Optimized Support Vector Machine (SVM) for Classification

Abstract Dementia is a cognitive disorder that mainly targets older adults. At present, dementia has no cure or prevention available. Scientists found that dementia symptoms might emerge as early as ten years before the onset of real disease. As a result, machine learning (ML) scientists developed various techniques for the early prediction of dementia using […]

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