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Significant challenges when introducing care robots in Swedish elder care.

Disability and rehabilitation. Assistive technology
INTRODUCTION: Care robots are machines, operating partly or completely autonomously, that are intended to assist older people and their caregivers. Care robots are seen as one part of the solution to the aging population, allowing fewer professional ...

Towards better process management in wastewater treatment plants: Process analytics based on SHAP values for tree-based machine learning methods.

Journal of environmental management
Understanding the mechanisms of pollutant removal in Wastewater Treatment Plants (WWTPs) is crucial for controlling effluent quality efficiently. However, the numerous treatment units, operational factors, and the underlying interactions between thes...

Translating polygenic risk scores for clinical use by estimating the confidence bounds of risk prediction.

Nature communications
A promise of genomics in precision medicine is to provide individualized genetic risk predictions. Polygenic risk scores (PRS), computed by aggregating effects from many genomic variants, have been developed as a useful tool in complex disease resear...

Artificial intelligence and the medical physics profession - A Swedish perspective.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
BACKGROUND: There is a continuous and dynamic discussion on artificial intelligence (AI) in present-day society. AI is expected to impact on healthcare processes and could contribute to a more sustainable use of resources allocated to healthcare in t...

[Machine learning and suicide prevention: is an algorithm the solution?].

Nederlands tijdschrift voor geneeskunde
Suicide is inherently difficult to predict. Epidemiological research identified many general risk factors such as a depression, but these predictors have limited predictive power. Machine learning offers a set of tools that can combine hundreds of pr...

Predicting women with depressive symptoms postpartum with machine learning methods.

Scientific reports
Postpartum depression (PPD) is a detrimental health condition that affects 12% of new mothers. Despite negative effects on mothers' and children's health, many women do not receive adequate care. Preventive interventions are cost-efficient among high...

Predicting vaginal birth after previous cesarean: Using machine-learning models and a population-based cohort in Sweden.

Acta obstetricia et gynecologica Scandinavica
INTRODUCTION: Predicting a woman's probability of vaginal birth after cesarean could facilitate the antenatal decision-making process. Having a previous vaginal birth strongly predicts vaginal birth after cesarean. Delivery outcome in women with only...

Ankle fracture classification using deep learning: automating detailed AO Foundation/Orthopedic Trauma Association (AO/OTA) 2018 malleolar fracture identification reaches a high degree of correct classification.

Acta orthopaedica
Background and purpose - Classification of ankle fractures is crucial for guiding treatment but advanced classifications such as the AO Foundation/Orthopedic Trauma Association (AO/OTA) are often too complex for human observers to learn and use. We h...

Developing a short-term prediction model for asthma exacerbations from Swedish primary care patients' data using machine learning - Based on the ARCTIC study.

Respiratory medicine
OBJECTIVE: The ability to predict impending asthma exacerbations may allow better utilization of healthcare resources, prevention of hospitalization and improve patient outcomes. We aimed to develop models using machine learning to predict risk of ex...

Machine learning-based mortality rate prediction using optimized hyper-parameter.

Computer methods and programs in biomedicine
OBJECTIVE AND BACKGROUND: The current scenario of the Pandemic of COVID-19 demands multi-channel investigations and predictions. A variety of prediction models are available in the literature. The majority of these models are based on extrapolating b...