AIMC Topic: Sweden

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Development and external validation of machine learning approaches for risk prediction of cardiovascular disease in individuals with schizophrenia: a nationwide Swedish and Danish study.

BMJ mental health
BACKGROUND: Currently available cardiovascular disease (CVD) risk prediction tools may underestimate the risk in individuals with schizophrenia. OBJECTIVE: To develop and externally validate 5-year CVD risk prediction models for people with schizophr...

Radiology Staff Experiences With Integrating Artificial Intelligence Into Radiology Practice in a Swedish Hospital: Qualitative Case Study.

JMIR formative research
BACKGROUND: The integration of artificial intelligence (AI) in radiology has advanced significantly, but research on how it affects the daily work of radiology staff is limited.

AI-Enhanced Social Robotic Versus Computer-Based Virtual Patients for Clinical Reasoning Training in Medical Education: Observational Crossover Cohort Study.

Journal of medical Internet research
BACKGROUND: Virtual patient (VP) simulations can be used to practice clinical reasoning (CR) in controlled learning environments. Traditional computer-based VP platforms often lack the authenticity and interactivity required for effective CR training...

Higher hospital level does not improve 30-day survival after road traffic accidents.

Scientific reports
Globally, road traffic accidents (RTAs) remain a major cause of death, particularly among individuals aged 15-30 years. While Sweden has been at the forefront of traffic safety through the Vision Zero initiative, in-hospital management remains crucia...

Worse survival despite indolent features for triple-negative invasive lobular carcinoma: a Swedish nationwide registry-based study.

Breast cancer research and treatment
PURPOSE: To evaluate differences in clinical outcomes, treatments received, recurrence, and sociodemographic characteristics in patients with triple-negative breast cancer (TNBC) classified as invasive lobular carcinoma (TNBC-ILC) or invasive carcino...

A machine learning tool for predicting newly diagnosed osteoporosis in primary healthcare in the Stockholm Region.

Scientific reports
Improving accuracy and timeliness for osteoporosis diagnosis could help prevent fragility fractures, morbidity, and mortality for older individuals. Osteoporosis is an often silent health condition, especially as regards vertebral fractures, and WHO ...

A deep learning approach to gender equality: Forecasting educational indicators with 1D-CNN aligned with SDG 5.

PloS one
Sustainable development goal (SDG) 5 focuses on gender equality and empowerment and it is considered as one of the most important SDGs. Therefore, this article presented a time series prediction model that predicts gender-related educational results ...

Prediction of Mini-Mental State Examination Scores for Cognitive Impairment and Machine Learning Analysis of Oral Health and Demographic Data Among Individuals Older Than 60 Years: Cross-Sectional Study.

JMIR medical informatics
BACKGROUND: As the older population grows, so does the prevalence of cognitive impairment, emphasizing the importance of early diagnosis. The Mini-Mental State Examination (MMSE) is vital in identifying cognitive impairment. It is known that degraded...

Machine-learning approach to atrial fibrillation prediction among individuals without prior cardiovascular diseases.

Open heart
BACKGROUND: There is a lack of atrial fibrillation (AF) prediction models tailored for individuals without prior cardiovascular diseases (CVDs) to facilitate early intervention. This study aimed to develop and validate an AF prediction model using ma...

Emergency medical services providers' perspectives on the use of artificial intelligence in prehospital identification of stroke- a qualitative study in Norway and Sweden.

BMC emergency medicine
BACKGROUND: Stroke is a large and increasing health challenge, leading to acquired physical disability and mortality. A rapid diagnostic assessment in the acute phase of a stroke is crucial and highly time dependent. Studies suggest that artificial i...