AIMC Topic: Sweden
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Association of Open vs Robot-Assisted Radical Cystectomy With Mortality and Perioperative Outcomes Among Patients With Bladder Cancer in Sweden.
JAMA network open
Apr 1, 2022
IMPORTANCE: Mortality rates resulting from bladder cancer have remained unchanged for more than 30 years. The surgical community has put hope in robot-assisted radical cystectomy (RARC) with intracorporeal urinary diversion (ICUD) in an effort to imp...
The entwinement of policy, design and care scripts: Providing alternative choice-dependency situations with care robots.
Sociology of health & illness
Jan 29, 2022
The use of robots to assist feeding has become important for people with an impaired arm function. Yet, despite large-scale dissemination strategies, it has proven difficult to sustain the use of this technology. This ethnographic study draws on the ...
Towards better process management in wastewater treatment plants: Process analytics based on SHAP values for tree-based machine learning methods.
Journal of environmental management
Oct 15, 2021
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
Sep 6, 2021
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...
Predicting spatiotemporally-resolved mean air temperature over Sweden from satellite data using an ensemble model.
Environmental research
Aug 28, 2021
Mapping of air temperature (Ta) at high spatiotemporal resolution is critical to reducing exposure assessment errors in epidemiological studies on the health effects of air temperature. In this study, we applied a three-stage ensemble model to estima...
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)
Jul 22, 2021
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...
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
May 26, 2021
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 and suicide prevention: is an algorithm the solution?].
Nederlands tijdschrift voor geneeskunde
May 12, 2021
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
Apr 12, 2021
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 suicide attempt or suicide death following a visit to psychiatric specialty care: A machine learning study using Swedish national registry data.
PLoS medicine
Nov 6, 2020
BACKGROUND: Suicide is a major public health concern globally. Accurately predicting suicidal behavior remains challenging. This study aimed to use machine learning approaches to examine the potential of the Swedish national registry data for predict...
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