AIMC Topic: Survival Rate
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Development of a web-based tool for estimating individualized survival curves in glioblastoma using clinical, mRNA, and tumor microenvironment features with fusion techniques.
Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
Oct 30, 2024
OBJECTIVE: Glioblastoma (GBM), one of the most common brain tumors, is known for its low survival rates and poor treatment responses. This study aims to create a robust predictive model that integrates multiple feature types, including clinical data,...
Deep Learning Predicts Lymphovascular Invasion Status in Muscle Invasive Bladder Cancer Histopathology.
Annals of surgical oncology
Oct 29, 2024
BACKGROUND: Lymphovascular invasion (LVI) is linked to poor prognosis in patients with muscle-invasive bladder cancer (MIBC). Accurately identifying the LVI status in MIBC patients is crucial for effective risk stratification and precision treatment....
Implementation of an AI Algorithm in Clinical Practice to Reduce Missed Incidental Pulmonary Embolisms on Chest CT and Its Impact on Short-Term Survival.
Investigative radiology
Oct 9, 2024
OBJECTIVES: A substantial number of incidental pulmonary embolisms (iPEs) in computed tomography scans are missed by radiologists in their daily routine. This study analyzes the radiological reports of iPE cases before and after implementation of an ...
Machine learning and statistical models to predict all-cause mortality in type 2 diabetes: Results from the UK Biobank study.
Diabetes & metabolic syndrome
Oct 5, 2024
AIMS: This study aims to compare the performance of contemporary machine learning models with statistical models in predicting all-cause mortality in patients with type 2 diabetes mellitus and to develop a user-friendly mortality risk prediction tool...
Prognostic insights after surgery for advances in understanding signet ring cell gastric cancer: a machine learning approach.
Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
Oct 3, 2024
BACKGROUND: Signet ring cell (SRC) gastric carcinoma is traditionally associated with a poor prognosis. However, the literature has presented contradictory results. Linear models are the standard statistical tools typically used to study these condit...
Predicting overall survival in anaplastic thyroid cancer using machine learning approaches.
European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
Sep 21, 2024
PURPOSE: Anaplastic thyroid carcinoma (ATC) is a highly aggressive and lethal thyroid cancer subtype with a poor prognosis. Recent advancements in machine learning (ML) have the potential to improve survival predictions. This study aimed to develop a...
Comparative evaluation of machine learning models in predicting overall survival for nasopharyngeal carcinoma using F-FDG PET-CT parameters.
Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
Sep 20, 2024
PURPOSE: The objective of this study is to assess the prognostic efficacy of F-fluorodeoxyglucose (F-FDG) positron emission tomography/computed tomography (PET-CT) parameters in nasopharyngeal carcinoma (NPC) and identify the best machine learning (M...
Explainable machine learning and online calculators to predict heart failure mortality in intensive care units.
ESC heart failure
Sep 19, 2024
AIMS: This study aims to develop explainable machine learning models and clinical tools for predicting mortality in patients in the intensive care unit (ICU) with heart failure (HF).
Multitask machine learning-based tumor-associated collagen signatures predict peritoneal recurrence and disease-free survival in gastric cancer.
Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Sep 14, 2024
BACKGROUND: Accurate prediction of peritoneal recurrence for gastric cancer (GC) is crucial in clinic. The collagen alterations in tumor microenvironment affect the migration and treatment response of cancer cells. Herein, we proposed multitask machi...
Using machine learning methods to investigate the impact of age on the causes of death in patients with early intrahepatic cholangiocarcinoma who underwent surgery.
Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
Sep 11, 2024
BACKGROUND: The impact of age on the causes of death (CODs) in patients with early-stage intrahepatic cholangiocarcinoma (ICC) who had undergone surgery was analyzed in this study.
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