AIMC Topic: Sweden
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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
Jul 28, 2025
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...
AI-Driven segmentation and morphogeometric profiling of epicardial adipose tissue in type 2 diabetes.
Cardiovascular diabetology
Jul 18, 2025
BACKGROUND: Epicardial adipose tissue (EAT) is associated with cardiometabolic risk in type 2 diabetes (T2D), but its spatial distribution and structural alterations remain understudied. We aim to develop a shape-aware, AI-based method for automated ...
A bird species occurrence dataset from passive audio recordings across dense urban areas in Gothenburg, Sweden.
Scientific data
Jul 10, 2025
Bird species occurrence datasets are a valuable resource for understanding the effects of urbanization on various biotic conditions (e.g., species occupancy and richness). Existing datasets offer promising opportunities to explore variations among ci...
External validation of a prediction model for disability and pain after lumbar disc herniation surgery: a prospective international registry-based cohort study.
Acta orthopaedica
Jul 7, 2025
BACKGROUND AND PURPOSE: We aimed to externally validate machine learning models developed in Norway by evaluating their predictive outcome of disability and pain 12 months after lumbar disc herniation surgery in a Swedish and Danish cohort.
Artificial Intelligence to Improve Clinical Coding Practice in Scandinavia: Crossover Randomized Controlled Trial.
Journal of medical Internet research
Jul 3, 2025
BACKGROUND: Clinical coding is critical for hospital reimbursement, quality assessment, and health care planning. In Scandinavia, however, coding is often done by junior doctors or medical secretaries, leading to high rates of coding errors. Artifici...
Uncovering nonlinear patterns in time-sensitive prehospital breathing emergencies: an exploratory machine learning study.
BMC medical informatics and decision making
Jun 3, 2025
BACKGROUND: Timely prehospital care is crucial for patients presenting with high-risk time-sensitive (HRTS) conditions. However, the interplay between response time and demographic factors in patients with breathing problems remains insufficiently un...
Clinical, genetic, and sociodemographic predictors of symptom severity after internet-delivered cognitive behavioural therapy for depression and anxiety.
BMC psychiatry
May 30, 2025
BACKGROUND: Internet-delivered cognitive behavioural therapy (ICBT) is an effective and accessible treatment for mild to moderate depression and anxiety disorders. However, up to 50% of patients do not achieve sufficient symptom relief. Identifying p...
Needs and Preferences of Swedish Young Adults for a Digital App Promoting Mental Health Literacy, Occupational Balance, and Peer Support: Qualitative Interview Study.
JMIR formative research
May 23, 2025
BACKGROUND: Young adults experience stressors in their transition to adulthood and are at increased risk of mental ill-health. This risk is compounded by young adults' low levels of mental health literacy and limited competencies in implementing stra...
Using machine learning involving diagnoses and medications as a risk prediction tool for post-acute sequelae of COVID-19 (PASC) in primary care.
BMC medicine
Apr 30, 2025
BACKGROUND: The aim of our study was to determine whether the application of machine learning could predict PASC by using diagnoses from primary care and prescribed medication 1 year prior to PASC diagnosis.
Predicting 30-day survival after in-hospital cardiac arrest: a nationwide cohort study using machine learning and SHAP analysis.
BMJ open
Apr 27, 2025
OBJECTIVE: In-hospital cardiac arrest (IHCA) presents a critical challenge with low survival rates and limited prediction tools. Despite advances in resuscitation, predicting 30-day survival remains difficult, and current methods lack interpretabilit...
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