How can AI enable personalized care?

When using image recognition and computer vision, AI has demonstrated that it can spot and diagnose better than doctors diseases such as cancer and alzheimer. This is thanks to deep learning, djich has increased image recognition accuracy bh more than 40% compared to traditional techniques.

Talking about personalised preventive care because that’s where I see a lot of value. Having a personalised nutrition, wellness, sleep and resilience coach(es)/sidekicks speaking to connected health devices would be a major very personalised use case. It knows users immediate routine, preferences, allergies etc. This could be a subset of the holy grailish personal assistant or a multi agent scenario (spawned by one instance of gpt). Any personal data could be ‘read in’ to it, say genomics

Having worked on an LLM 5 years ago, which was based on looking at symptoms, my insight was that many patients know their diagnoses but lack the combination of services and information to keep well, but there needs to be a dataset that allows them to find this. Then, we need to be able to analyse what services help each person. That why I co-founded @healthplace to solve this problem.

AI enables personalized care in prevention and wellness by using data from various sources to monitor individual health status and risk factors. It provides tailored interventions like goal setting, medication reminders, habit coaching, and health issue alerts to help manage chronic conditions such as diabetes, heart disease, and mental health problems, enhancing patient care and outcomes.

AI can help customised and personalized care by informing patients about their own body and health and what they need to avoid in order to be healthy and fit

AI, and even Generative AI, is now being used to speed up the discovery of new drugs, design of novel proteins, and healthcare strategies. While they still need to be validated, the initial parts of the process are massively sped up, freeing human experts' skills and enabling them to focus on the next steps of the process. A few months ago, a team at the University of Toronto announced that they now use "generative diffusion" (think - similar to Stable Diffusion) to discover novel proteins that would speed up drug development. This new field is called "Generative Biology", and the UoT research was recently published in Nature ("Score-based generative modelling for de novo protein design"). Exciting times for research and innovation!

AI can play a crucial role in addressing the ethical and policy challenges associated with personalized care. It can assist in evaluating the moral and social implications of AI applications, ensuring fairness, transparency, accountability, and respect for human dignity and rights. Furthermore, AI can provide evidence-based insights to inform the development of policies and regulations that support the responsible use of AI in healthcare. This includes risk assessment, bias mitigation, and the promotion of patient and stakeholder participation and empowerment. AI's ethical and policy contributions are integral to enabling personalized care while upholding ethical standards and legal compliance in healthcare.

Another key contribution is the use of AI for drug discovery and precision medecine. AI could significantly reduce the amount of time needed to discover and test new drugs thus radically changing the pharmaceutical industry.