How can artificial intelligence (AI) technology be used to achieve personalized medicine, so as to improve the accuracy of disease prevention, diagnosis and treatment?

• 1. The application of AI in disease prevention
• This section will explore the role of AI in genomics and epidemiology, and how the analysis of big data can be used to predict an individual's disease risk.
• ⦁ Investigate the potential of personalised health management solutions, utilising AI algorithms to monitor health indicators and provide early warnings.
• 2. The efficacy of AI-assisted diagnostic systems in the identification of significant illnesses, such as cardiovascular disease and cancer, is a crucial area of investigation.
• It is necessary to discuss how to enhance the trust of doctors in working with AI and increase their acceptance of AI recommendations.
• 3. The creation of bespoke treatment plans
• An investigation into the utilisation of AI in the formulation of personalised drug treatment plans is required. This may entail the analysis of patients' genomic information, with the objective of recommending the most appropriate drugs and doses.
• ⦁ Investigate the potential of AI in addressing the complexities inherent in medical records, particularly in the context of treating patients with multiple diseases.
• 4. Ethical and Privacy Issues
• The following questions must be addressed:
• 1. What are the ethical challenges that may be faced when using AI technology?
• 2. What are the implications of data privacy, algorithmic bias, and their impact on patient rights?
• It is essential to examine how a robust legal and ethical framework can be established to guarantee the secure and effective deployment of technology in the field of medicine.
• 5. Multidisciplinary collaboration and future development
• It is important to consider the value of interdisciplinary collaboration in the fields of medicine, computer science and data science for the advancement of personalized medicine.
• ⦁ Investigate prospective developments in the deployment of AI in healthcare and the means of furnishing researchers with enhanced training and education to capitalise on emerging technologies.