Unknown Organization (20240346524). System and Methods for Optimizing Human Factors and Usability Engineering in Life Sciences Using Artificial Intelligence simplified abstract
System and Methods for Optimizing Human Factors and Usability Engineering in Life Sciences Using Artificial Intelligence
Organization Name
Inventor(s)
Katia Mariel Rojas Garcia of New York NY (US)
System and Methods for Optimizing Human Factors and Usability Engineering in Life Sciences Using Artificial Intelligence - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240346524 titled 'System and Methods for Optimizing Human Factors and Usability Engineering in Life Sciences Using Artificial Intelligence
The patent application describes a system and methods for enhancing human factors (HF) and usability engineering in the life sciences and healthcare industry by integrating AI algorithms and techniques, ensuring adherence to key success factors, industry best practices, and regulatory demands. It includes software and hardware components, user interfaces, integration and communication functionalities, security mechanisms, and multimodality tools for documentation, analysis, reporting, AI-driven guidance, and predictive analytics. Fit-for-purpose AI features enhance decision-making and automate complex tasks, including risk analysis, guided by practical HF principles while continuously learning and adapting. The cloud-based infrastructure enables secure access and sharing of project data, supported by a database storing device specifications, user demographics, and usage scenarios. The system supports AI-driven features, mixed reality, and IoT, providing a scalable, end-to-end solution for regulatory compliance and successful application of HF, addressing limitations of traditional HF methods, enhancing efficiency, accuracy, and effectiveness.
- Integration of AI algorithms and techniques
- Adherence to key success factors, industry best practices, and regulatory demands
- Software and hardware components for documentation, analysis, reporting, and predictive analytics
- Cloud-based infrastructure for secure data access and sharing
- AI-driven features for decision-making and task automation
- Database storing device specifications, user demographics, and usage scenarios
Potential Applications: - Healthcare industry for improving usability and human factors in medical devices - Life sciences for enhancing user interfaces and communication functionalities
Problems Solved: - Addressing limitations of traditional human factors and usability engineering methods - Enhancing efficiency, accuracy, and effectiveness in the healthcare industry
Benefits: - Improved decision-making through AI-driven guidance - Automation of complex tasks such as risk analysis - Scalable solution for regulatory compliance and successful application of human factors
Commercial Applications: Title: Enhanced Human Factors and Usability Engineering System for Healthcare Industry This technology can be used in medical device development, pharmaceutical research, and healthcare software design to improve user experience and regulatory compliance.
Questions about the technology: 1. How does the integration of AI algorithms enhance decision-making in the healthcare industry? 2. What are the key benefits of using a cloud-based infrastructure for secure data access and sharing in life sciences and healthcare applications?
Original Abstract Submitted
system and methods for enhancing human factors (hf) and usability engineering in the life sciences and healthcare industry integrating ai algorithms and techniques, ensuring adherence to key success factors, industry best practices, and regulatory demands. it includes software and hardware components, user interfaces, integration and communication functionalities, security mechanisms, and multimodality tools for documentation, analysis, reporting, ai-driven guidance and predictive analytics. fit-for-purpose ai features enhance decision-making and automates complex tasks, including risk analysis, guided by practical hf principles while continuously learning and adapting. the cloud-based infrastructure enables secure access and sharing of project data, supported by a database storing device specifications, user demographics, and usage scenarios. the system supports ai-driven features, mixed reality, and iot, providing a scalable, end-to-end solution for regulatory compliance and successful application of hf, addressing limitations of traditional hf methods, enhancing efficiency, accuracy, and effectiveness.
