Yale researchers have developed a machine learning model, called Immunostruct, that can help scientists create more personalized vaccines, including vaccines for cancer. They described the tool in ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

The framework predicts how proteins will function with several interacting mutations and finds combinations that work well ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...

XRP sentiment hits extreme fear at 24 while institutional ETFs accumulated $424M in December alone, and $1.3 billion in 50 days. Machine learning models achieve 70-91% accuracy predicting crypto moves ...

@InProceedings{pstone_simba, author = {Hojoon Lee and Youngdo Lee and Takuma Seno and Donghu Kim and Peter Stone and Jaegul Choo}, title = {Hyperspherical Normalization for Scalable Deep Reinforcement ...

Abstract: Ovarian cancer is one of the most challenging cancers to detect early, often leading to poor survival rates. This study explores supervised and unsupervised machine learning and deep ...

ABSTRACT: Deep learning for time series sequence individual data instance classification can revolutionize computer assisted navigation by providing surgeons with accurate, real-time instrument ...

Abstract: Optimizing machine learning (ML) model performance relies heavily on appropriate data preprocessing techniques. Despite the widespread use of standardization and normalization, empirical ...