Cancer Prediction for Industrial IoT 4.0: A Machine Learning Perspective — 1st Edition

Cancer Prediction for Industrial IoT 4.0: A Machine Learning Perspective — First Edition

This interdisciplinary collection considers how connected devices, data analytics and machine-learning techniques are studied in the context of cancer-related prediction and health data processing.

Clinical and Research Topics

• Internet of Things and industrial data-system architectures.
• Sensor-derived or healthcare-related datasets.
• Machine-learning classification and prediction methods.
• Data preparation, feature selection and model evaluation.
• Cloud and edge computing concepts for analytics.
• Privacy, robustness, generalization and risks in clinical use.

Study Perspective

Predictive models need independent evaluation and careful clinical validation. Descriptions of connected systems or model accuracy should not be interpreted as evidence that a device or algorithm is approved for cancer diagnosis.

Who Should Read This Book?

Computer scientists, biomedical engineers, health informaticians and researchers working at the intersection of IoT and oncology.

Edition & Digital Product Details

Edition: First, as listed. Digital PDF reference rather than a live software system.

Digital format: English PDF eBook. Only the configured file is included; no physical publication or external service is supplied. This WordPress listing remains a draft until its digital file and publication details are confirmed.