Cox-SAGE: Enhancing Cox Proportional Hazards Model with Interpretable Graph Neural Networks for Cancer Prognosis

Information Science, Computer Science, Artificial Intelligence, Medicine, Hepatobiliary System, Oncology,
Cox proportional hazards model   cancer prognosis   graph neural networks   biomarker discovery   patient similarity graph  

1. Research Background and Disciplinary Frontiers Cancer prognosis analysis has always been a core research direction in the medical field. In recent years, with the widespread application of high-throughput sequencing technologies, scientists have been able to delve deeper into exploring molecular biomarkers and clinical characteristics of cancer ...

Testing and Overcoming the Limitations of Modular Response Analysis

Information Science, Computer Science, Artificial Intelligence, Life Sciences, Bioengineering, Genetics,
Modular Response Analysis   Regression   Network Inference   Lack of Fit   Convex Optimization   mraregress  

Research Background: New Challenges in Network Inference In the fields of modern molecular biology and systems biology, the precise elucidation of biomolecular networks—such as gene regulatory networks, protein interaction networks, and signaling networks—is regarded as central to understanding cellular processes, disease mechanisms, and drug actio...

A Comparison of Random Forest Variable Selection Methods for Regression Modeling of Continuous Outcomes

Information Science, Computer Science, Artificial Intelligence,
Random Forest   Variable Selection   Feature Selection   Regression Modeling   Machine Learning  

Background: The Importance of Variable Selection in Machine Learning Regression Models In recent years, the widespread application of machine learning in the fields of bioinformatics and data science has greatly driven the development of predictive modeling. Random forest (RF) regression, as a commonly used ensemble learning algorithm, has become a...

Exploring Diverse Approaches for Predicting Interferon-Gamma Release: Utilizing MHC Class II and Peptide Sequences

Information Science, Computer Science, Artificial Intelligence, Life Sciences, Biochemistry, Bioengineering, Immunology,
machine learning   T-cell response   immunology   predictive modeling   interferon-gamma   MHC class II   peptide sequences  

Academic Background and Research Significance In recent decades, therapeutic proteins have gained prominence as a research focus in the biopharmaceutical industry due to their huge potential in medicine. With their high targeting ability, therapeutic protein drugs are considered to offer solutions for many acute or chronic diseases (such as certain...

Consensus Statement on the Credibility Assessment of Machine Learning Predictors

Information Science, Computer Science, Artificial Intelligence, Medicine, Life Sciences, Bioengineering,
machine learning credibility   in silico medicine   causal knowledge assessment   regulatory science   error quantification   bias robustness  

1. Background: Machine Learning in Medicine and the Challenge of Credibility In recent years, the rapid development of Artificial Intelligence (AI) and Machine Learning (ML) technologies has brought about a tremendous transformation in the field of healthcare. Particularly in in silico medicine, machine learning predictors have become vital tools f...

Scaling of Hardware-Compatible Perturbative Training Algorithms

Engineering, Electrical Engineering, Information Science, Electronic Information, Computer Science, Artificial Intelligence,
perturbative training   hardware compatibility   gradient estimation   stochastic gradient descent   neuromorphic hardware   machine learning   computational efficiency  

With the rapid development of artificial intelligence (AI) technology, artificial neural networks (ANNs) have achieved significant success in multiple fields. However, traditional neural network training methods—especially the backpropagation algorithm—face numerous challenges in hardware implementation. Although the backpropagation algorithm is ef...