Peter Anderberg

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University of Skövde

Sweden

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Peter Anderberg is a Professor at the University of Skövde, Sweden. His research primarily focuses on gerontology, particularly in the areas of cognitive impairment, mental health, and the impact of technology on sleep health among older adults. He has contributed significantly to understanding biomarkers for Alzheimer's disease and has also explored the role of machine learning in chronic obstructive pulmonary disease. His recent work emphasizes data-driven approaches to health interventions and the relationship between oral health and cognitive function.

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Peter Anderberg

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Articles (21)

Temporal Associations Between Cognitive Impairment and Depression in Older Adults: A Longitudinal Analysis

Blood biomarkers for Alzheimer's disease: Reliable change and impacts of renal and blood–brain barrier function

Examining sleep health and its associations with technology use among older adults in Sweden: insights from a population-based study

Objective sleep monitoring at home in older adults: A scoping review

Predicting Depression in Older Adults: A Novel Feature Selection and Neural Network Framework

Vowel segmentation impact on machine learning classification for chronic obstructive pulmonary disease

Chronobiology in breathlessness across 24 h in people with persistent breathlessness

The long‐term effect on oral health and quality of life using a powered toothbrush in individuals with mild cognitive impairment. An intervention trial

Nursing Students’ Attitudes Toward Technology: Multicenter Cross-Sectional Study

Unveiling Cancer: A Data‐Driven Approach for Early Identification and Prediction Using F‐RUS‐RF Model

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

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

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

The prevalence of eHealth literacy and its relationship with perceived health status and psychological distress during Covid-19: a cross-sectional study of older adults in Blekinge, Sweden

Machine Learning for Dementia Prediction: A Systematic Review and Future Research Directions

Measurement of body temperature in the oral cavity with a temperature sensor integrated with a powered toothbrush

Sleep disturbance predicts worse cognitive performance in subsequent years: A longitudinal population-based cohort study

Self-Reported eHealth literacy among nursing students in Sweden and Poland: The eNursEd cross-sectional multicentre study

Antibiotic prescription using a digital decision support system: a register-based study of patients with hard-to-heal ulcers in Sweden

Comparing recalled versus experienced symptoms of breathlessness ratings

An Intelligent Learning System for Unbiased Prediction of Dementia Based on Autoencoder and Adaboost Ensemble Learning

Collaborators (10)

Jessica Berner

Ewa K Andersson

Patrik Midlöv

Anders Behrens

Johan Berglund

Sarah Nauman Ghazi

Ahmad Nauman Ghazi

Antonio I Cuesta-Vargas

Fermín Mayoral-Cleries

Jacob Sandberg

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