Cost-Effectiveness of Maintaining Higher Stem-Cell Collection Thresholds in the Chimeric Antigen Receptor T-Cell Era for Multiple Myeloma Predicting severe adverse events (SAEs) in oncology is ...

Abstract: We propose a data-driven modeling approach based on light gradient boosting machine (LightGBM) for remote cloud radio access network (C-RAN) architectures assisted by a directly modulated ...

Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...

Abstract: This study addresses the lack of comprehensive evaluations of feature scaling by systematically assessing 12 techniques, including less common methods such as VAST and Pareto, in 14 machine ...

A reproducible project for modeling and predicting Indian market indices (e.g., NIFTY, SENSEX) using FII (Foreign Institutional Investors) and DII (Domestic Institutional Investors) flows together ...

IN PATIENTS with cerebral infarction, machine learning models using neurophysiological and clinical data predicted ICU readmission. Logistic regression delivered the highest discrimination and offered ...

The development of low-cost, high-performance materials with enhanced transparency in the long-wavelength infrared (LWIR) region (800–1250 cm –1 /8–12.5 μm) is essential for advancing thermal imaging ...

ABSTRACT: Biogas is gaining prominence as a renewable energy source with significant potential to reduce greenhouse gas emissions and mitigate environmental impacts associated with fossil fuels. This ...

ABSTRACT: Biogas is gaining prominence as a renewable energy source with significant potential to reduce greenhouse gas emissions and mitigate environmental impacts associated with fossil fuels. This ...

Hi, here's the context regarding the three potential issues you mentioned earlier: First, my dataset size is in the millions (referring to the number of rows, sometimes close to ten million), and the ...