Explainable AI (XAI) methods & Cheat Sheet
Explainable AI refers to methods and techniques that help humans understand and interpret the predictions and decisions made by machine…
Category: Research Review
The Potentials and Challenges of Handling Missing Data in Multimodal Healthcare Data
Introduction Multimodal data in healthcare integrates diverse sources, such as medical imaging, wearable sensor readings, genomic information, and electronic health…
Deep Learning Applications in Partial Differential Equations
Deep learning has emerged as a powerful tool in solving and analyzing Partial Differential Equations (PDEs), offering innovative approaches for…
Principal Components for Neural Network Initialization: A Novel Approach to Explainability and Efficiency
Brief summary: While PCA is traditionally employed for dimensionality reduction and denoising before training, this preprocessing can complicate the interpretability…
Vision-Language Models in Healthcare: Unlocking Multimodal Intelligence for Medical Applications
In summary: Vision-Language Models (VLMs) in healthcare represent a significant technological advancement, offering a promising pathway to integrate and analyze…
DPER: Direct Parameter Estimation for Randomly Missing Data
The paper “DPER: Direct Parameter Estimation for Randomly Missing Data,” by Thu Nguyen, Khoi Minh Nguyen-Duy, Duy Ho Minh Nguyen, Binh T. Nguyen, Bruce Alan Wade introduces a novel methodology…
Combining datasets to increase sample size
Detailed information can be found in Combining datasets to improve model fitting or its presentation slide. Summary: The key points…