Explainable AI (XAI) exists to close this gap. It is not just a trend or an afterthought; XAI is an essential product capability required for responsibly scaling AI. Without it, AI remains a powerful ...
Healthcare is a complex socio-technical system, not a purely technical environment. Clinical decisions are shaped not only by ...
This course explores the field of Explainable AI (XAI), focusing on techniques to make complex machine learning models more transparent and interpretable. Students will learn about the need for XAI, ...
Using Real-World Data for Machine-Learning Algorithms to Predict the Treatment Response in Advanced Melanoma: A Pilot Study for Personalizing Cancer Care This study aims to investigate the impact of ...
Cognitive computing represents an innovative frontier within computer science, merging artificial intelligence, machine learning, and computational ...
n this study, 773 untreated breast cancer patients from all over China were collected and followed up for at least 5 years. We obtained clinical data from 773 cases, RNA sequencing data from 752 cases ...
The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to ...
With over 20 years in the field of software engineering, I have observed the evolution of AI from a theoretical concept to an integral part of modern business transformation. AI is no longer just an ...
Most current autonomous driving systems rely on single-agent deep learning models or end-to-end neural networks. While ...
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