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Survival Analysis

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Survival analysis using deep learning with medical imaging.

The international journal of biostatistics
There is widespread interest in using deep learning to build prediction models for medical imaging data. These deep learning methods capture the local structure of the image and require no manual feature extraction. Despite the importance of modeling...

Estimation of separable direct and indirect effects in a continuous-time illness-death model.

Lifetime data analysis
In this article we study the effect of a baseline exposure on a terminal time-to-event outcome either directly or mediated by the illness state of a continuous-time illness-death process with baseline covariates. We propose a definition of the corres...

18F-FDG PET/CT Image Deep Learning Predicts Colon Cancer Survival.

Contrast media & molecular imaging
Colon cancer is a type of cancer that begins in the large intestine. In the process of efficacy evaluation, postoperative recurrence prediction and metastasis monitoring of colon cancer, traditional medical image analysis methods are highly dependent...

Multi-event survival analysis through dynamic multi-modal learning for ICU mortality prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Survival analysis is widely applied for assessing the expected duration of patient status towards event occurrences such as mortality in healthcare domain, which is generally considered as a time-to-event problem. Patients w...

Deep Survival Analysis With Clinical Variables for COVID-19.

IEEE journal of translational engineering in health and medicine
OBJECTIVE: Millions of people have been affected by coronavirus disease 2019 (COVID-19), which has caused millions of deaths around the world. Artificial intelligence (AI) plays an increasing role in all areas of patient care, including prognostics. ...

Self-supervised learning-based Multi-Scale feature Fusion Network for survival analysis from whole slide images.

Computers in biology and medicine
Understanding prognosis and mortality is critical for evaluating the treatment plan of patients. Advances in digital pathology and deep learning techniques have made it practical to perform survival analysis in whole slide images (WSIs). Current meth...

Survival analysis of localized prostate cancer with deep learning.

Scientific reports
In recent years, data-driven, deep-learning-based models have shown great promise in medical risk prediction. By utilizing the large-scale Electronic Health Record data found in the U.S. Department of Veterans Affairs, the largest integrated healthca...

Neural Networks for Survival Prediction in Medicine Using Prognostic Factors: A Review and Critical Appraisal.

Computational and mathematical methods in medicine
Survival analysis deals with the expected duration of time until one or more events of interest occur. Time to the event of interest may be unobserved, a phenomenon commonly known as right censoring, which renders the analysis of these data challengi...

A Framework for Using Real-World Data and Health Outcomes Modeling to Evaluate Machine Learning-Based Risk Prediction Models.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: We propose a framework of health outcomes modeling with dynamic decision making and real-world data (RWD) to evaluate the potential utility of novel risk prediction models in clinical practice. Lung transplant (LTx) referral decisions in ...

HIV-positive patients with oral Kaposi's sarcoma: An overall survival analysis of 31 patients.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: The aim of this study was to evaluate the influence of viral load and lymphocyte count on survival of patients who presented with human immunodeficiency virus (HIV)-associated oral Kaposi's sarcoma.