AIMC Topic: Risk

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BCR-Net: A deep learning framework to predict breast cancer recurrence from histopathology images.

PloS one Apr 4, 2023
Breast cancer is the most common malignancy in women, with over 40,000 deaths annually in the United States alone. Clinicians often rely on the breast cancer recurrence score, Oncotype DX (ODX), for risk stratification of breast cancer patients, by u...
Humans Deep Learning Female Breast Breast Neoplasms Risk Ki-67 Antigen
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A multimodal deep learning system to distinguish late stages of AMD and to compare expert vs. AI ocular biomarkers.

Scientific reports Feb 16, 2022
Within the next 1.5 decades, 1 in 7 U.S. adults is anticipated to suffer from age-related macular degeneration (AMD), a degenerative retinal disease which leads to blindness if untreated. Optical coherence tomography angiography (OCTA) has become a p...
Predictive Value of Tests Tomography, Optical Coherence Macular Degeneration Risk Expert Testimony Choroidal Neovascularization Severity of Illness Index Humans Deep Learning ROC Curve Neural Networks, Computer Diagnosis, Differential Biomarkers
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Deep learning segmentation and quantification method for assessing epicardial adipose tissue in CT calcium score scans.

Scientific reports Feb 10, 2022
Epicardial adipose tissue volume (EAT) has been linked to coronary artery disease and the risk of major adverse cardiac events. As manual quantification of EAT is time-consuming, requires specialized training, and is prone to human error, we develope...
Coronary Artery Disease Calcium Heart Disease Risk Factors Risk Humans Pericardium Deep Learning Tomography, X-Ray Computed Adipose Tissue Organ Size
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Machine learning prediction model of acute kidney injury after percutaneous coronary intervention.

Scientific reports Jan 14, 2022
Acute kidney injury (AKI) after percutaneous coronary intervention (PCI) is associated with a significant risk of morbidity and mortality. The traditional risk model provided by the National Cardiovascular Data Registry (NCDR) is useful for predictin...
Aged Aged, 80 and over Male Middle Aged Research Design Acute Kidney Injury Female Registries Percutaneous Coronary Intervention Japan Risk Postoperative Complications Logistic Models Models, Statistical Area Under Curve Humans Machine Learning Forecasting
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Conservatism predicts aversion to consequential Artificial Intelligence.

PloS one Dec 20, 2021
Artificial intelligence (AI) has the potential to revolutionize society by automating tasks as diverse as driving cars, diagnosing diseases, and providing legal advice. The degree to which AI can improve outcomes in these and other domains depends on...
Risk Educational Status Politics Adult Male Humans Attitude to Computers Trust Artificial Intelligence Female
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Real-Time Stress Level Feedback from Raw Ecg Signals for Personalised, Context-Aware Applications Using Lightweight Convolutional Neural Network Architectures.

Sensors (Basel, Switzerland) Nov 24, 2021
Human stress is intricately linked with mental processes such as decision making. Public protection practitioners, including Law Enforcement Agents (LEAs), are forced to make difficult decisions during high-pressure operations, under strenuous circum...
Neural Networks, Computer Humans Feedback Electrocardiography Risk
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Machine learning approach for the prediction of postpartum hemorrhage in vaginal birth.

Scientific reports Nov 19, 2021
Postpartum hemorrhage is the leading cause of maternal morbidity. Clinical prediction of postpartum hemorrhage remains challenging, particularly in the case of a vaginal birth. We studied machine learning models to predict postpartum hemorrhage. Wome...
Young Adult Adult Middle Aged Deep Learning Adolescent ROC Curve Logistic Models Pregnancy Female Infant, Newborn Reproducibility of Results Humans Delivery, Obstetric Neural Networks, Computer Labor, Obstetric Area Under Curve Models, Theoretical Machine Learning Tokyo Support Vector Machine False Positive Reactions Models, Statistical Risk Postpartum Hemorrhage
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A weighted patient network-based framework for predicting chronic diseases using graph neural networks.

Scientific reports Nov 19, 2021
Chronic disease prediction is a critical task in healthcare. Existing studies fulfil this requirement by employing machine learning techniques based on patient features, but they suffer from high dimensional data problems and a high level of bias. We...
Data Interpretation, Statistical Translational Research, Biomedical Programming Languages Risk Pulmonary Disease, Chronic Obstructive Male Cardiovascular Diseases Chronic Disease Humans Databases, Factual Female Neural Networks, Computer Reproducibility of Results Machine Learning Software Algorithms
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The impact of recency and adequacy of historical information on sepsis predictions using machine learning.

Scientific reports Oct 21, 2021
Sepsis is a major public and global health concern. Every hour of delay in detecting sepsis significantly increases the risk of death, highlighting the importance of accurately predicting sepsis in a timely manner. A growing body of literature has ex...
Humans Machine Learning Algorithms Sepsis Prognosis Risk
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Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review.

BMJ (Clinical research ed.) Oct 20, 2021
OBJECTIVE: To assess the methodological quality of studies on prediction models developed using machine learning techniques across all medical specialties.
Machine Learning Models, Statistical Data Interpretation, Statistical Bias Humans Multivariate Analysis Risk Clinical Decision Rules
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