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Processing Decision Tree Data Using Internet of Things (IoT) and Artificial Intelligence Technologies with Special
Latefa Hamad Al Fryan1, Mahasin Ibrahim Shomo2, Malik Bader Alazzam3
1Educational Technology, Faculty of Education, Princess Nourah University, Saudi Arabia.
Biomed Research International
|July 8, 2022
Summary
Artificial intelligence decision trees offer effective medical data processing. These AI and Internet of Things (IoT) applications improve diagnosis, treatment, and hospital management.
Area of Science:
- Medical Informatics
- Computer Science
Background:
- Alternative medical treatments are increasingly available.
- A need exists for tools to aid doctors in patient diagnosis and treatment planning.
- Artificial intelligence (AI) offers powerful data analysis capabilities.
Purpose of the Study:
- To explore the application of decision trees in medical contexts.
- To review alternative induction strategies for decision tree models.
- To demonstrate the utility of decision trees in hospital and epidemic management.
Main Methods:
- Utilizing decision tree algorithms for data classification and prediction.
- Integrating Internet of Things (IoT) technology with AI for medical data processing.
- Analyzing large datasets to identify patterns and support decision-making.
Main Results:
- Decision trees proved effective in processing complex medical data.
- AI and IoT integration enhanced the performance of medical applications.
- The study demonstrated successful classification and prediction using decision tree models.
Conclusions:
- Decision trees, powered by AI and IoT, are highly effective for medical data analysis.
- These technologies can significantly improve diagnostic accuracy and treatment planning.
- The researchers recommend broader adoption of AI and IoT in healthcare and other fields.
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