What can you learn about AI and robotics in healthcare?

The Bio-Inspired aspect of AI where bringing embedded and distributed processing and storage capability to the front-end sensing node will significantly improve the point of care (POC) testing and diagnosis at affordable costs and rapid access to personalized care. Through a careful co-design of front-end hardware, firmware and the software layers , an intelligent and portable bio-sensing platform can be devised which is not limited by the bio-functionalization and the burden of specificity is taken over by the electronic computation power. These devices would only utilize the bandwidth to share the data with the AI server when an enhanced reasoning is required, extending endurance of the sensor node.

I'm not sure if I agree with the statement: "AI ... perform tasks that normally require human intelligence". The AI we have today can not YET do that kind of resoning (AGI will eventually get there some day). In health care, AI is mostly used for pattern identification and classification. Whether it's medical images or biological markers etc... AI Diagnosis and decisions are made upon statistical inference and not "human intelligence".

According to the EU AI Act proposal an Ai system is defined as a system designed to operate with varying levels of autonomy and that can, for explicit or implicit objectives, generate output such as predictions, recommendations, or decisions influencing physical or virtual environments. The border then between robotc system and an AI system definitions need to be clearly adressed otherwise this will be a major issue for compliance and a source of confusion in the future...

With an aging global population and an increased focus on improving the quality of life for the elderly, AI and robotics are and will be instrumental in transforming senior care. AI and robotics present significant opportunities for enhancing senior care both in the institution & care facilities sector as well as in the Aging in place sector.

Major AI and robotics applications for senior care: Personal Care Assistants: assisting seniors with daily tasks, such as getting in and out of bed, bathing, or dressing. One well-known example is the Toyota Human Support Robot (HSR) which can pick up objects from the floor, fetch items, and more. Companionship Robots: Devices like Paro, ElliQ and Pepper provide companionship, recognize and respond to human emotions, thus helping in reducing feelings of loneliness and isolation among the elderly. Cognitive Assistance: Providing reminders for medications, appointments, and daily activities. This is especially valuable for seniors with memory ailments like Alzheimer’s or dementia.

1. Health care is a highly regulated industry and regulation will be applied to both the AI and the robotics. Addressing regulatory approvals will be essential. 2. There will be several ethical issues regarding data privacy, security, patient selection and patient rights and informed consent. 3. How insurance and funding systems will pay for AI/robot services will be essential for this to be viable.

1. Liability is one challenge facing AI & Robotics in health care. Who is juridically liable when/if the AI or autonomous robots make a mistake and kill a person? Will it be accepted by the general populous? - even if the probability of it happening is lower than for a human doctor (not everyone, for example, accepts vaccines because of rare side effects) 2. Unfair regulation: The regulatory process (scientific research excluded) is very expensive. Large corporations have deep pockets and can undergo such process giving them an unfair advantage towards small start-ups. This might have a negative effect on the economy by inhibiting innovation and reducing market diversity.

AI and robotics challenges in senior care: 1. Not all senior care staff are familiar with or have been trained to use advanced technology. This could mean extensive training, which requires both time and resources. 2. Technophobia: There's a fear of technology among some care providers. They might worry that they'll be replaced by machines or that they'll be unable to operate the new systems. 3. Loss of Human Touch: Staff might be concerned that the more they rely on technology, the less human interaction the seniors will have, which is crucial for their emotional well-being.

I agree and propose that specific and available courses be identified. This could be a task for ChatGPT and assessed by experts for quality.

If you're interested in this or any other scientific or technical subject, why not enroll in a university course? You'll have qualified lecturers, some of them in the fore front of the field doing research. You can be more certain that the quality is high (at least more than online courses).

In today's digital era, tools like ChatGPT offer a powerful avenue for rapidly developing prototypes geared towards healthcare. For instance, leveraging the capabilities of generative AI models such as ChatGPT, or even alternatives like Google Bard, in tandem with the WhatsApp API can revolutionize the way patients access information, resources, and medical appointments. The potency of merging these two platforms – Generative AI and WhatsApp API – is particularly evident in regions where WhatsApp boasts a penetration rate of over 90%. Many countries in Latin America serve as prime examples. Such integrations not only promise enhanced accessibility but also foster a seamless communication channel between medical professionals and patients.

I came across blue brain technology, basically transferring human intelligence to a super computer which can be used even after a person's death during my college days and was inspired and even worked on making a mini prototype of the same trying to use it for various medical applications

Interoperability and Standardizing data formats Discussing the challenges related to interoperability and data exchange between different AI and robotics systems in healthcare can be insightful. As the healthcare landscape becomes more complex with multiple systems and devices, ensuring seamless communication and data sharing is crucial. For instance, a surgical robot might need to communicate with diagnostic AI tools and post-operative monitoring devices. Standardizing data formats, communication protocols, and security measures becomes paramount to ensure a cohesive and efficient healthcare ecosystem.