Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...
Section 101 eligibility remains one of the most unpredictable and frequently contested areas of U.S. patent practice, particularly for ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...
Can deep learning catch chronic illness before symptoms show? This article explores how time-aware neural networks are reshaping early detection and care planning for conditions like diabetes and COPD ...
The line between human and artificial intelligence is growing ever more blurry. Since 2021, AI has deciphered ancient texts ...
Introduction You are tasked to lead a 40-truck convoy resupplying combat troops at the front during large-scale combat ...
According to Daniel Acton, chief technology officer at Accelera Digital Group, the sophisticated use cases promised by AI require a robust foundation of high-quality data.
Abstract: The ability to accurately predict the house price is fundamental within the real estate sector as it provides useful information to potential buyers, sellers, investors, and policymakers.
Abstract: The Wafer Acceptance Test (WAT) is a significant quality control measurement in the semiconductor industry. However, because the WAT process can be time-consuming and expensive, sampling ...
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