We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance ...
Integrating AI models with the medical domain is challenging as it involves more complex workflows compared to traditional machine learning operations (MLOps). Requirements such as model performance ...
Awurum, N.P. (2025) Next-Generation Cyber Defense: AI-Powered Predictive Analytics for National Security and Threat Resilience. Open Access Library Journal, 12, 1-17. doi: 10.4236/oalib.1114210 .
The rushed and uneven rollout of A.I. has created a fog in which it is tempting to conclude that there is nothing to see here ...
In this tutorial, we explore how to harness Apache Spark’s techniques using PySpark directly in Google Colab. We begin by setting up a local Spark session, then progressively move through ...
Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...
Quantum computing is set to redefine data security, AI, and cloud infrastructure. This in-depth research explores how post-quantum cryptography, quantum AI acceleration, and hybrid quantum-cloud ...
Researchers utilize 2D electrical resistivity imaging and borehole data to estimate the N60-value of soils with k-means clustering technique Thailand's northern regions, characterized by complex ...
Torgny Fornstedt describes how machine learning can work in practice for oligonucleotide analysis. Recent advances in machine learning have significantly improved the ability to evaluate data quality ...
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