Dynamic prediction with time‐dependent marker in survival analysis using supervised functional principal component analysis
Sign Up to like & getrecommendations! Published in 2022 at "Statistics in Medicine"
DOI: 10.1002/sim.9433
Abstract: Time‐varying biomarkers reflect important information on disease progression over time. Dynamic prediction for event occurrence on a real‐time basis, utilizing time‐varying information, is crucial in making accurate clinical decisions. Functional principal component analysis (FPCA) has… read more here.
Keywords: time; functional principal; dynamic prediction; analysis ... See more keywords
Dynamic prediction of patient outcomes during ongoing cardiopulmonary resuscitation.
Sign Up to like & getrecommendations! Published in 2017 at "Resuscitation"
DOI: 10.1016/j.resuscitation.2016.09.007
Abstract: PURPOSE The probability of the return of spontaneous circulation (ROSC) and subsequent favourable outcomes changes dynamically during advanced cardiac life support (ACLS). We sought to model these changes using time-to-event analysis in out-of-hospital cardiac arrest… read more here.
Keywords: probability; resuscitation dynamic; subsequent outcomes; resuscitation ... See more keywords
Dynamic prediction of overall survival for patients with high-grade extremity soft tissue sarcoma.
Sign Up to like & getrecommendations! Published in 2018 at "Surgical oncology"
DOI: 10.1016/j.suronc.2018.09.003
Abstract: PURPOSE There is increasing interest in personalized prediction of disease progression for soft tissue sarcoma patients. Currently, available prediction models are limited to predictions from time of surgery or diagnosis. This study updates predictions of… read more here.
Keywords: sarcoma; soft tissue; time; dynamic prediction ... See more keywords
Integrating landmark modeling framework and machine learning algorithms for dynamic prediction of tuberculosis treatment outcomes
Sign Up to like & getrecommendations! Published in 2022 at "Journal of the American Medical Informatics Association : JAMIA"
DOI: 10.1093/jamia/ocac003
Abstract: 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.… read more here.
Keywords: machine; dynamic prediction; framework; treatment outcomes ... See more keywords
Dynamic prediction of relapse in patients with acute leukemias after allogeneic transplantation: Joint model for minimal residual disease
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Laboratory Hematology"
DOI: 10.1111/ijlh.13328
Abstract: Relapse remains the leading cause of treatment failure after allogeneic hematopoietic stem cell transplantation (alloHSCT) in leukemia. Numerous investigations have demonstrated that minimal residual disease (MRD) before or after alloHSCT is prognostic of relapse risk.… read more here.
Keywords: minimal residual; relapse; residual disease; transplantation ... See more keywords
Dynamic prediction model to identify young children at high risk of future overweight: Development and internal validation in a cohort study
Sign Up to like & getrecommendations! Published in 2020 at "Pediatric Obesity"
DOI: 10.1111/ijpo.12647
Abstract: Summary Background Primary prevention of overweight is to be preferred above secondary prevention, which has shown moderate effectiveness. Objective To develop and internally validate a dynamic prediction model to identify young children in the general… read more here.
Keywords: validation; age; prediction model; model ... See more keywords
Dynamic Prediction for Accuracy Maintaining Reliability of Superprecision Rolling Bearing in Service
Sign Up to like & getrecommendations! Published in 2018 at "Shock and Vibration"
DOI: 10.1155/2018/7396293
Abstract: A dynamic prediction method for accuracy maintaining reliability (AMR) of superprecision rolling bearings (SPRBs) in service is proposed by effectively fusing chaos theory and grey system theory and applying stochastic processes. In this paper, the… read more here.
Keywords: accuracy; service; dynamic prediction; reliability ... See more keywords
Dynamic Prediction of Internet Financial Market Based on Deep Learning
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DOI: 10.1155/2022/1465394
Abstract: P2P lending is an important part of Internet finance, which is popular among users because of its efficiency, low cost, wide range, and ease of operation. The problem of predicting loan defaults is affected by… read more here.
Keywords: prediction internet; internet; dynamic prediction; financial market ... See more keywords
Dynamic Prediction of Patient Outcomes in the Intensive Care Unit: A Scoping Review of the State-of-the-Art.
Sign Up to like & getrecommendations! Published in 2023 at "Journal of intensive care medicine"
DOI: 10.1177/08850666231166349
Abstract: INTRODUCTION Intensive care units (ICUs) are high-pressure, complex, technology-intensive medical environments where patient physiological data are generated continuously. Due to the complexity of interpreting multiple signals at speed, there are substantial opportunities and significant potential… read more here.
Keywords: intensive care; review; patient outcomes; dynamic prediction ... See more keywords
Dynamic prediction of competing risk events using landmark sub-distribution hazard model with multiple longitudinal biomarkers
Sign Up to like & getrecommendations! Published in 2020 at "Statistical Methods in Medical Research"
DOI: 10.1177/0962280220921553
Abstract: The cause-specific cumulative incidence function quantifies the subject-specific disease risk with competing risk outcome. With longitudinally collected biomarker data, it is of interest to dynamically update the predicted cumulative incidence function by incorporating the most… read more here.
Keywords: landmark; risk; model; dynamic prediction ... See more keywords
Dynamic Prediction of Non-Neutral SARS-Cov-2 Variants Using Incremental Machine Learning
Sign Up to like & getrecommendations! Published in 2022 at "Studies in health technology and informatics"
DOI: 10.3233/shti220550
Abstract: In this work we show that Incremental Machine Learning can be used to predict the classification of emerging SARS-CoV-2 lineages, dynamically distinguishing between neutral variants and non-neutral ones, i.e. variants of interest or variants of… read more here.
Keywords: non neutral; dynamic prediction; machine learning; incremental machine ... See more keywords