AIMC Topic: Predictive Value of Tests

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Electrocardiogram Delineation Using Deep Neural Networks.

Studies in health technology and informatics May 16, 2022
BACKGROUND: In recent years, there has been a rising interest in the application of deep neural networks (DNN) for the delineation of the electrocardiogram (ECG).
Predictive Value of Tests Neural Networks, Computer Electrocardiography
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Revival and Revision of Right Ventricular Assessment by Machine Learning.

JACC. Cardiovascular imaging May 1, 2022
Heart Ventricles Humans Artificial Intelligence Machine Learning Algorithms Predictive Value of Tests
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Predicting peritoneal recurrence and disease-free survival from CT images in gastric cancer with multitask deep learning: a retrospective study.

The Lancet. Digital health May 1, 2022
BACKGROUND: Peritoneal recurrence is the predominant pattern of relapse after curative-intent surgery for gastric cancer and portends a dismal prognosis. Accurate individualised prediction of peritoneal recurrence is crucial to identify patients who ...
Artificial Intelligence Retrospective Studies Tomography, X-Ray Computed Humans Neoplasm Recurrence, Local Peritoneal Neoplasms Disease-Free Survival Stomach Neoplasms Deep Learning Predictive Value of Tests
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Integrating landmark modeling framework and machine learning algorithms for dynamic prediction of tuberculosis treatment outcomes.

Journal of the American Medical Informatics Association : JAMIA Apr 13, 2022
OBJECTIVE: This study aims to establish an informative dynamic prediction model of treatment outcomes using follow-up records of tuberculosis (TB) patients, which can timely detect cases when the current treatment plan may not be effective.
Humans Machine Learning Algorithms Treatment Outcome Tuberculosis Predictive Value of Tests
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Development of a Machine Learning Model Using Limited Features to Predict 6-Month Mortality at Treatment Decision Points for Patients With Advanced Solid Tumors.

JCO clinical cancer informatics Mar 1, 2022
PURPOSE: Patients with advanced solid tumors may receive intensive treatments near the end of life. This study aimed to create a machine learning (ML) model using limited features to predict 6-month mortality at treatment decision points (TDPs).
Adult Neoplasms Predictive Value of Tests DNA-Binding Proteins Humans Machine Learning Prognosis
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Defining "Better Prediction" by Machine-Learning Models Toward Clinical Application.

JACC. Cardiovascular imaging Mar 1, 2022
Cardiovascular Diseases Predictive Value of Tests Humans Machine Learning
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Imaging With Deep Learning: Sharpening the Cutting Edge.

JACC. Cardiovascular imaging Mar 1, 2022
Humans Algorithms Deep Learning Electrocardiography Predictive Value of Tests Ventricular Dysfunction, Left
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Neural network-based integration of polygenic and clinical information: development and validation of a prediction model for 10-year risk of major adverse cardiac events in the UK Biobank cohort.

The Lancet. Digital health Feb 1, 2022
BACKGROUND: In primary cardiovascular disease prevention, early identification of high-risk individuals is crucial. Genetic information allows for the stratification of genetic predispositions and lifetime risk of cardiovascular disease. However, tow...
Risk Assessment Genotype Predictive Value of Tests Heart Disease Risk Factors United Kingdom Neural Networks, Computer Phenotype Cardiovascular Diseases Humans
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International Validation of the SORG Machine-learning Algorithm for Predicting the Survival of Patients with Extremity Metastases Undergoing Surgical Treatment.

Clinical orthopaedics and related research Feb 1, 2022
BACKGROUND: The Skeletal Oncology Research Group machine-learning algorithms (SORG-MLAs) estimate 90-day and 1-year survival in patients with long-bone metastases undergoing surgical treatment and have demonstrated good discriminatory ability on inte...
Postoperative Period Extremities Humans Adult Male Middle Aged Female Machine Learning Bone Neoplasms Aged Prognosis Aged, 80 and over Taiwan Predictive Value of Tests
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Identification of cardiovascular high-risk groups from dynamic retinal vessel signals using untargeted machine learning.

Cardiovascular research Jan 29, 2022
AIMS: Dynamic retinal vessel analysis (DVA) provides a non-invasive way to assess microvascular function in patients and potentially to improve predictions of individual cardiovascular (CV) risk. The aim of our study was to use untargeted machine lea...
Venules Cause of Death Signal Processing, Computer-Assisted Cardiovascular Diseases Female Renal Dialysis Photic Stimulation Workflow Humans Middle Aged Aged Treatment Outcome Retinal Vessels Machine Learning Risk Assessment Light Cluster Analysis Arterioles Male Vasodilation Predictive Value of Tests Heart Disease Risk Factors Kidney Failure, Chronic
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