AIMC Topic: Survival Analysis
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Alzheimer's disease risk prediction using machine learning for survival analysis with a comorbidity-based approach.
Scientific reports
Aug 6, 2025
Alzheimer's disease (AD) presents a pressing global health challenge, demanding improved strategies for early detection and understanding its progression. In this study, we address this need by employing survival analysis techniques to predict transi...
Open-radiomics: a collection of standardized datasets and a technical protocol for reproducible radiomics machine learning pipelines.
BMC medical imaging
Aug 4, 2025
BACKGROUND: As an important branch of machine learning pipelines in medical imaging, radiomics faces two major challenges namely reproducibility and accessibility. In this work, we introduce open-radiomics, a set of radiomics datasets along with a co...
Machine learning analysis of survival outcomes in breast cancer patients treated with chemotherapy, hormone therapy, surgery, and radiotherapy.
Scientific reports
Jul 10, 2025
Breast cancer continues to be a leading cause of death among women in the world. The prediction of survival outcomes based on treatment modalities, i.e., chemotherapy, hormone therapy, surgery, and radiation therapy is an essential step towards perso...
Comparative study of five-year cervical cancer cause-specific survival prediction models based on SEER data.
Scientific reports
Jul 2, 2025
Cervical cancer (CC) is a major cause of mortality in women, with stagnant survival rates, highlighting the need for improved prognostic models. This study aims to develop and compare machine learning models for predicting five-year cause-specific su...
Comparison of AI chatbot predicted and realworld survival outcomes in hepatocellular carcinoma.
Scientific reports
Jul 1, 2025
This study compares survival predictions made by an artificial intelligence (AI) based chatbot with real-world data in hepatocellular carcinoma (HCC) patients. It aims to evaluate the reliability and accuracy of AI technologies in HCC prognosis. A re...
Survival analysis for sepsis patients: A machine learning approach to feature selection and predictive modeling.
Scientific reports
Jul 1, 2025
Sepsis is a life-threatening condition that presents substantial challenges to healthcare and pharmacological management due to its high mortality rates and complex patient responses. Accurately predicting patient outcomes is essential for optimizing...
The Role of PANoptosis-Related Genes in Predicting Breast Cancer Survival and Immune Prospect.
BioMed research international
May 28, 2025
The function of PANoptosis in breast cancer (BC) remains indistinct. We constructed a nomogram model to predict the prognosis of BC to identify high-risk patients and help them receive more accurate treatment. We used Cox regression and least absol...
Using interpretable survival analysis to assess hospital length of stay.
BMC health services research
May 22, 2025
Accurate in-hospital length of stay prediction is a vital quality metric for hospital leaders and health policy decision-makers. It assists with decision-making and informs hospital operations involving factors such as patient flow, elective cases, a...
Personalized therapeutic strategies and prognosis for advanced laryngeal squamous cell carcinoma: Insights from machine learning models.
American journal of otolaryngology
Apr 24, 2025
PURPOSE: Despite the development of diverse treatment options, there has been an increase in mortality rates for laryngeal squamous cell carcinoma (LSCC). Our research employed survival analysis and machine learning (ML) techniques to evaluate the im...
Data-driven survival modeling for breast cancer prognostics: A comparative study with machine learning and traditional survival modeling methods.
PloS one
Apr 22, 2025
Background This investigation delves into the potential application of data-driven survival modeling approaches for prognostic assessments of breast cancer survival. The primary objective is to evaluate and compare the ability of machine learning (ML...
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