Journal of neurology, neurosurgery, and psychiatry
Jul 1, 2014
Artificial neural networks (ANNs) effectively analyze non-linear data sets. The aimed was A review of the relevant published articles that focused on the application of ANNs as a tool for assisting clinical decision-making in neurosurgery. A literatu...
Studies in health technology and informatics
Apr 8, 2025
Non-specific clinical biomarkers have been shown to help identify prognostic risks in cancer patients. However, the accuracy of prognostic biomarkers for predicting survival in patients with metastatic castration-resistant prostate cancer (mCRPC) sti...
Studies in health technology and informatics
Apr 8, 2025
Chronic lymphocytic leukemia (CLL) exhibits a heterogeneous clinical course. Prognostic markers that impact patient outcomes have been identified, including MYC gene abnormalities. This study investigates machine learning (ML) models for predicting s...
Multi-omics data often suffer from the "big $p$, small $n$" problem where the dimensionality of features is significantly larger than the sample size, making the integration of multi-omics data for survival analysis of a specific cancer particularly ...
Accurate cancer prognosis is essential for personalized clinical management, guiding treatment strategies and predicting patient survival. Conventional methods, which depend on the subjective evaluation of histopathological features, exhibit signific...
With an increasing focus on precision medicine in medical research, numerous studies have been conducted in recent years to clarify the relationship between treatment effects and patient characteristics. The treatment effects for patients with differ...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Survival analysis plays a pivotal role in healthcare, particularly in analyzing time-to-event data such as in disease progression, treatment efficacy, and drug development. Traditional methods in survival analysis often face a trade-off: they either ...
Recent studies have extensively used deep learning algorithms to analyze gene expression to predict disease diagnosis, treatment effectiveness, and survival outcomes. Survival analysis studies on diseases with high mortality rates, such as cancer, ar...
Studies in health technology and informatics
May 23, 2024
This study explores endometrial cancer (EC) within the broader context of oncogynecology, focusing on 3,845 EC patients at the Almazov National Research Center. The research analyzes clinical data, employing machine learning techniques like random fo...