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Survival Rate

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Deep learning models for predicting the survival of patients with medulloblastoma based on a surveillance, epidemiology, and end results analysis.

Scientific reports
Medulloblastoma is a malignant neuroepithelial tumor of the central nervous system. Accurate prediction of prognosis is essential for therapeutic decisions in medulloblastoma patients. We analyzed data from 2,322 medulloblastoma patients using the SE...

Deep learning models for predicting the survival of patients with hepatocellular carcinoma based on a surveillance, epidemiology, and end results (SEER) database analysis.

Scientific reports
Hepatocellular carcinoma (HCC) is a common malignancy with poor survival and requires long-term follow-up. Hence, we collected information on patients with Primary Hepatocellular Carcinoma in the United States from the Surveillance, Epidemiology, and...

Artificial Intelligence Assessment of Biological Age From Transthoracic Echocardiography: Discrepancies with Chronologic Age Predict Significant Excess Mortality.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
BACKGROUND: Age and sex can be estimated using artificial intelligence on the basis of various sources. The aims of this study were to test whether convolutional neural networks could be trained to estimate age and predict sex using standard transtho...

Comparison of deep learning models to traditional Cox regression in predicting survival of colon cancer: Based on the SEER database.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: In this study, a deep learning algorithm was used to predict the survival rate of colon cancer (CC) patients, and compared its performance with traditional Cox regression.

Survival estimation of oral cancer using fuzzy deep learning.

BMC oral health
BACKGROUND: Oral cancer is a deadly disease and a major cause of morbidity and mortality worldwide. The purpose of this study was to develop a fuzzy deep learning (FDL)-based model to estimate the survival time based on clinicopathologic data of oral...

Predicting in-hospital mortality among patients admitted with a diagnosis of heart failure: a machine learning approach.

ESC heart failure
Existing risk prediction models for hospitalized heart failure patients are limited. We identified patients hospitalized with a diagnosis of heart failure between 7 May 2013 and 26 April 2022 from a large academic, quaternary care medical centre (tra...

Completion of Pembrolizumab in Advanced Non-Small Cell Lung Cancer-Real World Outcomes After Two Years of Therapy (COPILOT).

Clinical lung cancer
BACKGROUND: Seminal trials with first-line pembrolizumab for metastatic non-small cell lung cancer (NSCLC) mandated a maximum two-years treatment. We describe real-world outcomes of a multi-site Australian cohort of patients who completed two-years o...

Machine Learning-Based Prediction of Pathological Responses and Prognosis After Neoadjuvant Chemotherapy for Non-Small-Cell Lung Cancer: A Retrospective Study.

Clinical lung cancer
BACKGROUND: Neoadjuvant chemotherapy has variable efficacy in patients with non-small-cell lung cancer (NSCLC), yet reliable noninvasive predictive markers are lacking. This study aimed to develop a radiomics model predicting pathological complete re...