Tension: Companies have more customer data than ever, yet struggle to balance immediate revenue needs against long-term ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Numerous challenges, including the variable anatomy of SC, ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

Advanced K-Means clustering system for customer analytics and segmentation using machine learning. Includes RFM analysis, business insights, and actionable marketing strategies. - ...

Modern enterprises depend on reliable, fast connectivity to deliver a consistent customer experience. It can make the difference to efficient operations, favorable customer interactions and sustained ...

Introduction: The choroid plexus (CP), a critical structure for cerebrospinal fluid (CSF) production, has been increasingly recognized for its involvement in Alzheimer’s disease (AD). Accurate ...

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...

Background: Radiomics based on automatic segmentation of CT images has emerged as a highly promising approach for differentiating adrenal adenomas from metastases in clinical practice; however, its ...

ABSTRACT: In this paper, a novel multilingual OCR (Optical Character Recognition) method for scanned papers is provided. Current open-source solutions, like Tesseract, offer extremely high accuracy ...

This project performs customer segmentation using K-Means Clustering, a powerful unsupervised machine learning technique. By analyzing customer purchasing behavior, the model segments customers into ...