AIMC Topic: Sweden

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Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms.

JAMA network open Mar 2, 2020
IMPORTANCE: Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives.
Algorithms Female Sweden Aged Adult Humans Artificial Intelligence Early Detection of Cancer Mammography Radiology Radiologists Image Interpretation, Computer-Assisted Sensitivity and Specificity Breast Neoplasms Middle Aged Deep Learning United States
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Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study.

The Lancet. Oncology Jan 8, 2020
BACKGROUND: An increasing volume of prostate biopsies and a worldwide shortage of urological pathologists puts a strain on pathology departments. Additionally, the high intra-observer and inter-observer variability in grading can result in overtreatm...
Biopsy Image Interpretation, Computer-Assisted Reproducibility of Results Sweden Humans Aged Artificial Intelligence Middle Aged Male Prospective Studies Diagnosis, Computer-Assisted Predictive Value of Tests Prostatic Neoplasms Neoplasm Grading
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A modern approach to identifying and characterizing child asthma and wheeze phenotypes based on clinical data.

PloS one Dec 30, 2019
'Asthma' is a complex disease that encapsulates a heterogeneous group of phenotypes and endotypes. Research to understand these phenotypes has previously been based on longitudinal wheeze patterns or hypothesis-driven observational criteria. The aim ...
Leukocyte Count Respiratory Sounds Twins Diseases in Twins Adolescent Child Regression Analysis Eosinophils Risk Factors Medical History Taking Asthma Male Severity of Illness Index Machine Learning Data Analysis Biomarkers Humans Female Sweden
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Recent advances in Swedish and Spanish medical entity recognition in clinical texts using deep neural approaches.

BMC medical informatics and decision making Dec 23, 2019
BACKGROUND: Text mining and natural language processing of clinical text, such as notes from electronic health records, requires specific consideration of the specialized characteristics of these texts. Deep learning methods could potentially mitigat...
Humans Neural Networks, Computer Natural Language Processing Electronic Health Records Data Mining Language Sweden Deep Learning
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A validation of machine learning-based risk scores in the prehospital setting.

PloS one Dec 13, 2019
BACKGROUND: The triage of patients in prehospital care is a difficult task, and improved risk assessment tools are needed both at the dispatch center and on the ambulance to differentiate between low- and high-risk patients. This study validates a ma...
Humans Machine Learning Prospective Studies Female Sweden Needs Assessment Ambulances Risk Assessment Hospitalization ROC Curve Aged Triage Male Emergency Service, Hospital Middle Aged Critical Care
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Re: Functional and Oncologic Outcomes between Open and Robotic Radical Prostatectomy at 24-Month Follow-up in the Swedish LAPPRO Trial.

The Journal of urology Sep 12, 2019
Robotics Robotic Surgical Procedures Prostatectomy Humans Sweden Male Follow-Up Studies
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Training machine learning models to predict 30-day mortality in patients discharged from the emergency department: a retrospective, population-based registry study.

BMJ open Aug 10, 2019
OBJECTIVES: The aim of this work was to train machine learning models to identify patients at end of life with clinically meaningful diagnostic accuracy, using 30-day mortality in patients discharged from the emergency department (ED) as a proxy.
Time Factors Logistic Models Emergency Service, Hospital Registries Patient Discharge Young Adult Adult Male Middle Aged Mortality Humans Machine Learning Retrospective Studies Electronic Health Records Female Sweden Aged Aged, 80 and over
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Readmission prediction using deep learning on electronic health records.

Journal of biomedical informatics Jul 24, 2019
Unscheduled 30-day readmissions are a hallmark of Congestive Heart Failure (CHF) patients that pose significant health risks and escalate care cost. In order to reduce readmissions and curb the cost of care, it is important to initiate targeted inter...
Cost Savings Humans Neural Networks, Computer Electronic Health Records Female Sweden Risk Factors Models, Statistical Aged Patient Discharge Aged, 80 and over Male Heart Failure Deep Learning Patient Readmission Time Factors Expert Systems Computational Biology
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Robot-assisted Radical Prostatectomy-So Successful Because It Is Better or Better Because It Is So Successful?

European urology oncology Sep 15, 2018
Humans Sweden Male Follow-Up Studies Robotics Robotic Surgical Procedures Prostatectomy
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Machine Learning Methods Improve Prognostication, Identify Clinically Distinct Phenotypes, and Detect Heterogeneity in Response to Therapy in a Large Cohort of Heart Failure Patients.

Journal of the American Heart Association Apr 12, 2018
BACKGROUND: Whereas heart failure (HF) is a complex clinical syndrome, conventional approaches to its management have treated it as a singular disease, leading to inadequate patient care and inefficient clinical trials. We hypothesized that applying ...
Cardiovascular Agents Adrenergic beta-Antagonists Heart Failure Diuretics Aged Prognosis Humans Ventricular Function, Left Angiotensin Receptor Antagonists Aged, 80 and over Retrospective Studies Machine Learning Stroke Volume Angiotensin-Converting Enzyme Inhibitors Survival Rate Female Algorithms Middle Aged Male Reproducibility of Results Phenotype Follow-Up Studies Sweden Registries
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