Intelligent Systems in Healthcare Monitoring

Интеллектуальные системы в мониторинге здравоохранения
Srinath Doss, S Pratibha Sree, C. Kishor Kumar Reddy, Avula Mahathi
2024-10-11

Healthcare 6.0artificial intelligence (AI)intelligent systems in healthcaremachine learning (ML)predictive analytics
Artificial Intelligence (AI) and data analysis in healthcare enhance patient outcomes through improvements in diagnosis and treatment planning. By offering healthcare practitioners real-time guidance, systems to support clinical decisions optimise the delivery of care Healthcare 6.0 relies heavily on intelligent systems capable of advanced problem-solving, pattern recognition, and real-time insights. These systems are made possible by AI and ML. Virtual health assistants, robotic surgery, personalized medicine, and predictive analytics are a few examples of intelligent systems in the healthcare industry. Utilizing AI, these solutions boost patient out-comes, decrease errors, and streamline clinical procedures. Healthcare 6.0's intelligent systems' effects on clinical practice, patient involvement, healthcare economics, and related fields are covered in detail in the sections that follow. Stakeholders will acquire a thorough grasp of the threats, opportunities, and current de-velopments in this revolutionary era of healthcare through in-depth examination
1
AI and data analysis in healthcare improve patient outcomes by enhancing diagnosis and treatment planning.
2
Examples of intelligent systems in healthcare include virtual health assistants, robotic surgery, personalized medicine, and predictive analytics, which boost outcomes and reduce errors.
3
Healthcare 6.0 depends on intelligent systems (AI/ML) for advanced problem-solving, pattern recognition, and real-time insights.
4
Real-time AI-driven clinical decision support systems optimize care delivery for healthcare practitioners.
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The paper examines impacts of Healthcare 6.0 intelligent systems on clinical practice, patient engagement, healthcare economics, and associated risks and opportunities.

Intelligent systems in healthcare (AI/ML-based clinical decision support, virtual health assistants, robotic surgery, personalized medicine, predictive analytics)

Their effects on clinical practice, patient engagement, healthcare outcomes and economics, including real-time guidance, error reduction, workflow optimization, and opportunities/risks in Healthcare 6.0

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2024-10-11
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Srinath Doss
S Pratibha Sree
C. Kishor Kumar Reddy
Avula Mahathi
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