AIMC Topic: Sweden
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Predicting vaginal birth after previous cesarean: Using machine-learning models and a population-based cohort in Sweden.
Acta obstetricia et gynecologica Scandinavica
Oct 31, 2020
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
Oct 26, 2020
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...
Key insights in the AIDA community policy on sharing of clinical imaging data for research in Sweden.
Scientific data
Oct 6, 2020
Development of world-class artificial intelligence (AI) for medical imaging requires access to massive amounts of training data from clinical sources, but effective data sharing is often hindered by uncertainty regarding data protection. We describe ...
A machine-learning algorithm for neonatal seizure recognition: a multicentre, randomised, controlled trial.
The Lancet. Child & adolescent health
Aug 27, 2020
BACKGROUND: Despite the availability of continuous conventional electroencephalography (cEEG), accurate diagnosis of neonatal seizures is challenging in clinical practice. Algorithms for decision support in the recognition of neonatal seizures could ...
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...
Pattern Recognition, Automated
Smoking
False Positive Reactions
Tobacco Use Disorder
Observer Variation
Medical Informatics
Automation
Natural Language Processing
Bayes Theorem
Data Mining
Algorithms
Research Design
Electronic Health Records
ROC Curve
Support Vector Machine
Reproducibility of Results
Sweden
Humans
Machine Learning
Software
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 ...
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