AIMC Topic: Sweden
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Using machine learning for predicting cervical cancer from Swedish electronic health records by mining hierarchical representations.
PloS one
Aug 21, 2020
Electronic health records (EHRs) contain rich documentation regarding disease symptoms and progression, but EHR data is challenging to use for diagnosis prediction due to its high dimensionality, relative scarcity, and substantial level of noise. We ...
Machine learning-based mortality rate prediction using optimized hyper-parameter.
Computer methods and programs in biomedicine
Aug 18, 2020
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...
Range of Radiologist Performance in a Population-based Screening Cohort of 1 Million Digital Mammography Examinations.
Radiology
Jul 28, 2020
Background There is great interest in developing artificial intelligence (AI)-based computer-aided detection (CAD) systems for use in screening mammography. Comparative performance benchmarks from true screening cohorts are needed. Purpose To determi...
Natural language processing and machine learning to enable automatic extraction and classification of patients' smoking status from electronic medical records.
Upsala journal of medical sciences
Jul 22, 2020
BACKGROUND: The electronic medical record (EMR) offers unique possibilities for clinical research, but some important patient attributes are not readily available due to its unstructured properties. We applied text mining using machine learning to en...
Humans
Pattern Recognition, Automated
Smoking
ROC Curve
False Positive Reactions
Tobacco Use Disorder
Support Vector Machine
Research Design
Data Mining
Natural Language Processing
Machine Learning
Electronic Health Records
Bayes Theorem
Observer Variation
Software
Reproducibility of Results
Medical Informatics
Sweden
Algorithms
Automation
Identifying the relative importance of predictors of survival in out of hospital cardiac arrest: a machine learning study.
Scandinavian journal of trauma, resuscitation and emergency medicine
Jun 25, 2020
INTRODUCTION: Studies examining the factors linked to survival after out of hospital cardiac arrest (OHCA) have either aimed to describe the characteristics and outcomes of OHCA in different parts of the world, or focused on certain factors and wheth...
Significant challenges when introducing care robots in Swedish elder care.
Disability and rehabilitation. Assistive technology
Jun 13, 2020
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 ...
Risk of a second wave of Covid-19 infections: using artificial intelligence to investigate stringency of physical distancing policies in North America.
International orthopaedics
Jun 5, 2020
PURPOSE: Accurately forecasting the occurrence of future covid-19-related cases across relaxed (Sweden) and stringent (USA and Canada) policy contexts has a renewed sense of urgency. Moreover, there is a need for a multidimensional county-level appro...
Olle Höök Lectureship 2019: The changing world of stroke rehabilitation.
Journal of rehabilitation medicine
Apr 29, 2020
The paper presents a summary of the Olle Höök lecture, which was presented at the Baltic North-Sea Forum in Oslo, Sweden, in October 2019. The paper aims to provide a worldwide picture of stroke, developments in this field, and the evolution of strok...
Predicting mental health problems in adolescence using machine learning techniques.
PloS one
Apr 6, 2020
BACKGROUND: Predicting which children will go on to develop mental health symptoms as adolescents is critical for early intervention and preventing future, severe negative outcomes. Although many aspects of a child's life, personality, and symptoms h...
Machine-Learning prediction of comorbid substance use disorders in ADHD youth using Swedish registry data.
Journal of child psychology and psychiatry, and allied disciplines
Apr 1, 2020
BACKGROUND: Children with attention-deficit/hyperactivity disorder (ADHD) have a high risk for substance use disorders (SUDs). Early identification of at-risk youth would help allocate scarce resources for prevention programs.
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