[APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN REHABILITATION]

Area of Science:

• Medical Technology
• Computer Science
• Rehabilitation Medicine

Background:

• Artificial intelligence (AI) applications are increasingly prevalent in modern medicine.
• Machine learning (ML), a subset of AI, enables systems to learn from data and make predictions.
• AI and ML hold significant potential to advance clinical decision-making in rehabilitation.

Purpose of the Study:

• To explore the role of AI and ML in enhancing rehabilitation processes.
• To investigate AI's utility in diagnosing functional impairments.
• To examine the development of personalized rehabilitation programs using AI.

Main Methods:

• Review of current AI and ML methodologies applicable to healthcare.
• Analysis of AI's potential in diagnostic and treatment protocol development.
• Exploration of human-machine interfaces for functional compensation.

Main Results:

• AI and ML can significantly improve clinical decision-making in rehabilitation.
• These technologies can aid in the accurate diagnosis of functional impairments.
• AI facilitates the creation of tailored rehabilitation programs and protocols.

Conclusions:

• AI and ML are poised to revolutionize rehabilitation by personalizing care and improving outcomes.
• Integration of AI into rehabilitation can enhance body function recovery and compensation.
• Future applications include advanced human-machine interfaces for restorative and compensatory purposes.