AIMC Topic: Proportional Hazards Models

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Using Natural Language Processing to Identify Home Health Care Patients at Risk for Diagnosis of Alzheimer's Disease and Related Dementias.

Journal of applied gerontology : the official journal of the Southern Gerontological Society Mar 31, 2024
This study aimed to: (1) validate a natural language processing (NLP) system developed for the home health care setting to identify signs and symptoms of Alzheimer's disease and related dementias (ADRD) documented in clinicians' free-text notes; (2) ...
Natural Language Processing Medicare Datasets as Topic Male United States Longitudinal Studies Proportional Hazards Models Aged Humans Aged, 80 and over Reproducibility of Results
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ResDeepSurv: A Survival Model for Deep Neural Networks Based on Residual Blocks and Self-attention Mechanism.

Interdisciplinary sciences, computational life sciences Mar 15, 2024
Survival analysis, as a widely used method for analyzing and predicting the timing of event occurrence, plays a crucial role in the medicine field. Medical professionals utilize survival models to gain insight into the effects of patient covariates o...
Algorithms Deep Learning Survival Analysis Proportional Hazards Models Humans Neural Networks, Computer
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Examining arterial pulsation to identify and risk-stratify heart failure subjects with deep neural network.

Physical and engineering sciences in medicine Feb 15, 2024
Hemodynamic parameters derived from pulse wave analysis have been shown to predict long-term outcomes in patients with heart failure (HF). Here we aimed to develop a deep-learning based algorithm that incorporates pressure waveforms for the identific...
Deep Learning ROC Curve Pulse Wave Analysis Heart Failure Middle Aged Proportional Hazards Models Humans Arteries Risk Assessment Female Neural Networks, Computer Case-Control Studies Aged Male
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An artificial intelligence-driven predictive model for pediatric allogeneic hematopoietic stem cell transplantation using clinical variables.

European journal of haematology Feb 9, 2024
BACKGROUND: Hematopoietic stem cell transplantation (HSCT) is a procedure with high morbidity and mortality. Identifying patients for maximum benefit and risk assessment is crucial in the decision-making process. This has led to the development of pr...
Female Male Infant Humans Artificial Intelligence Prognosis Hematopoietic Stem Cell Transplantation Transplantation, Homologous Proportional Hazards Models Kaplan-Meier Estimate Adolescent Child, Preschool Child
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Quantified treatment effect at the individual level is more indicative for personalized radical prostatectomy recommendation: implications for prostate cancer treatment using deep learning.

Journal of cancer research and clinical oncology Feb 1, 2024
BACKGROUND: There are potential uncertainties and overtreatment existing in radical prostatectomy (RP) for prostate cancer (PCa) patients, thus identifying optimal candidates is quite important.
Prostate Proportional Hazards Models Prostatectomy Deep Learning Prostatic Neoplasms Humans Prostate-Specific Antigen Retrospective Studies Male
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Integrating Machine Learning and Mendelian Randomization Determined a Functional Neurotrophin-Related Gene Signature in Patients with Lower-Grade Glioma.

Molecular biotechnology Jan 23, 2024
Recent researches reported that neurotrophins can promote glioma growth/invasion but the relevant model for predicting patients' survival in Lower-Grade Gliomas (LGGs) lacked. In this study, we adopted univariate Cox analysis, LASSO regression, and m...
Humans Female Brain Neoplasms Machine Learning Prognosis Neoplasm Grading Proportional Hazards Models Homeodomain Proteins Nerve Growth Factors Glioma Sulfotransferases Male DNA Copy Number Variations Polymorphism, Single Nucleotide Mendelian Randomization Analysis Gene Expression Regulation, Neoplastic
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Sample size and predictive performance of machine learning methods with survival data: A simulation study.

Statistics in medicine Nov 10, 2023
Prediction models are increasingly developed and used in diagnostic and prognostic studies, where the use of machine learning (ML) methods is becoming more and more popular over traditional regression techniques. For survival outcomes the Cox proport...
Proportional Hazards Models Neural Networks, Computer Machine Learning Computer Simulation Sample Size Humans
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A support vector machine-based cure rate model for interval censored data.

Statistical methods in medical research Nov 8, 2023
The mixture cure rate model is the most commonly used cure rate model in the literature. In the context of mixture cure rate model, the standard approach to model the effect of covariates on the cured or uncured probability is to use a logistic funct...
Survival Analysis Proportional Hazards Models Computer Simulation Support Vector Machine Models, Statistical Humans Algorithms
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The use of deep learning models to predict progression-free survival in patients with neuroendocrine tumors.

Future oncology (London, England) Jul 27, 2023
The RAISE project assessed whether deep learning could improve early progression-free survival (PFS) prediction in patients with neuroendocrine tumors. Deep learning models extracted features from CT scans from patients in CLARINET (NCT00353496) (n...
Progression-Free Survival Humans Proportional Hazards Models Tomography, X-Ray Computed Neuroendocrine Tumors Deep Learning
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Deep learning model for predicting the survival of patients with primary gastrointestinal lymphoma based on the SEER database and a multicentre external validation cohort.

Journal of cancer research and clinical oncology Jul 10, 2023
PURPOSE: Due to the rarity of primary gastrointestinal lymphoma (PGIL), the prognostic factors and optimal management of PGIL have not been clearly defined. We aimed to establish prognostic models using a deep learning algorithm for survival predicti...
Random Forest Gastrointestinal Neoplasms SEER Program Deep Learning Logistic Models Lymphoma Aged Male Middle Aged Survival Analysis Proportional Hazards Models Humans Prognosis Female
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