Conclusion

Abstract

This conclusion presents some closing thoughts on the concepts covered in the preceding chapters of this book. The book presents computational approaches for intelligent health data analysis, with applications in medicine, health care, biology, pharmacology, and related fields. Intelligent Data Analysis (IDA) accelerates the analysis and use of healthcare data. IDA analyzes data and deduces the mechanisms generated using specific statistical, pattern recognition, machine learning, data abstraction, and visualization capabilities. The book discusses artificial intelligence in healthcare methodologies and tools for bridging the gap between data collection and data comprehension. It emphases problem-solving inside healthcare facilities for the purpose of managing patient information, data warehousing, intelligent alarms, and competent monitoring. The book also discusses various alternatives and methods for effectively expanding existing implementations in a variety of domains, including graduate course classrooms, research facilities, healthcare services, non- destructive investigations, ambient intelligence, medical education, and healthcare facility plants.

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