Manuscript Topics

Recently, the integration of Artificial Intelligence (AI) in bioengineering heralds a transformative leap forward for medical science and patient care. AI's ability to process vast datasets beyond human capability has paved the way for groundbreaking advancements. From robots conducting surgery to algorithms predicting disease patterns, the synergy of these fields is setting new frontiers. However, the path to integrating AI into medical robotics, imaging, and personalized therapeutics is fraught with multifaceted challenges. These span from technical obstacles, such as the need for high-fidelity algorithms capable of real-time processing, to ethical concerns around patient data security and algorithmic transparency. In medical robotics, the delicate balance between autonomy and human oversight raises questions about liability and trust in machine precision. Imaging, while vastly improved by AI, still must overcome hurdles in standardization and interpretation across heterogeneous medical systems. Personalized therapeutics, perhaps the most promising, must navigate the complexities of integrating genomic data with clinical practice, ensuring equitable access while tailoring individual treatment.

This special issue is therefore poised at the innovative strides and research at the intersection of AI and bioengineering. The authors from different backgrounds (such as artificial intelligence, robotics, computer science, and bioengineering) are welcome to share their theoretical and experimental solutions or frameworks to enhance medical robotics, imaging, and personalized therapeutics. Review articles are also encouraged.

The subjects concerned are:
• AI-driven algorithms for predictive diagnostics and personalized treatment plans
• Breakthroughs in AI-powered medical robotics for surgery and rehabilitation
• Innovations in biomedical imaging through machine learning techniques
• Customized drug development and delivery systems using AI models
• AI and IoT for remote monitoring and health management
• Ethical implications and regulations of AI in medical applications
• Computational strategies for complex biological data analysis
• Integration of AI in tissue engineering and regenerative medicine
• Smart prosthetics and implants enhanced by AI
• Machine learning in genomic medicine for personalized therapeutics

Keywords: artificial intelligence in medicine, medical robotics automation, AI-enhanced imaging technologies, personalized medicine AI algorithms, bioengineering AI challenges, genomic data analysis, ethical AI in healthcare, AI in surgical robotics, machine learning for diagnostics, AI-driven therapeutic development

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