Kommande
bokomslag Social Network Analysis and Mining Applications in Healthcare and Anomaly Detection
Data & IT

Social Network Analysis and Mining Applications in Healthcare and Anomaly Detection

Mehmet Kaya Sleiman Alhajj Kashfia Sailunaz Min-Yuh Day

Inbunden

3329:-

Funktionen begränsas av dina webbläsarinställningar (t.ex. privat läge).

  • 336 sidor
  • 2025
This book is an excellent source of knowledge for readers interested in the latest developments in social network analysis and mining, particularly with applications in healthcare and anomaly detection. It covers topics such as sensitivity to noise in features, enhancing fraud detection in financial systems, measuring the echo-chamber phenomenon, detecting comorbidity, and evaluating the effectiveness of mitigative and preventative actions on viral spread in small communities using agent-based stochastic simulations. Additionally, it discusses predicting behavior, measuring and identifying influence, analyzing the impact of COVID-19 on various social aspects, and using UNet for handling various skin conditions. This book helps readers develop their own perspectives on adapting social network concepts to various applications. It also demonstrates how to use various machine learning techniques for tackling challenges in social network analysis and mining.
  • Författare: Mehmet Kaya, Sleiman Alhajj, Kashfia Sailunaz, Min-Yuh Day
  • Format: Inbunden
  • ISBN: 9783031752032
  • Språk: Engelska
  • Antal sidor: 336
  • Utgivningsdatum: 2025-01-30
  • Förlag: Springer International Publishing AG