Your personal AI doctor: Data & AI in the medical field

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The medical industry is one that is sensitive in many areas: While data and AI can help drive a revolution, we also need to be incredibly careful about cybersecurity in this industry, since it can cost lives and risk national security in case of a breach. This may have limited the interest of some tech specialists in the medical field as they have a decreased risk appetite. Today I want to discuss one of the most notable ways in which AI is used to manage healthcare, thanks to innovators who made it their business to improve this delicate industry:

Programmed computers do not forget

 

Right now people are making use of artificial intelligence to assist them in managing their medical problems better. It is especially those people living alone with chronic illnesses who tend to neglect themselves especially when it comes to taking that very important chronic medication and they can really benefit from having a little robotic medical assistant around who not only tells them when to take their medication but who will also frequently ask them how they are feeling at different points during the day. This can keep a sick person more alert and remind them of the steps they have to take to ensure that their physical condition remains constant throughout the day. Here we are talking especially about people with a history of heart problems or other serious illnesses such as type II diabetes. If those people are not punctual with their medication this can lead to very serious medical problems and in a worst-case scenario they might even die.

The doctors substitute

 

Unfortunately doctors cannot look after a single patient 24 hours a day while they are at home. This will not be cost effective or an inefficient use of the time of that Doctor. However a small and relatively inexpensive robotic medical assistant can do their job efficiently, tirelessly and in a professional manner. This medical assistant will remind the patient when they need to do some needed exercises, when they need to take their medication or when they may need to rest to reduce unnecessary physical stress. The robotic medical assistant will frequently ask the heart patient whether their breathing is okay and because of this constant prodding the chances that the patient will become careless or negligent is reduced substantially. It is remarkable what can be accomplished with machine learning also known as artificial intelligence not just within industries but also as far as medical care concerned. In the case of a known heart patient the robotic medical assistant is actually asking questions which comes from a predetermined list which is often used by physicians when they are treating heart patients.

AI and psychological problems

 

The robotic assistant is not only there to ensure that medication is taken or to ensure that the patient is physically well but they also have to look at the psychological condition of those patients. Therefore they are programmed to analyze the responses which they receive from patients in order to determine problems such as anxiety, depression and other problems often related to patients with heart conditions. However to hear the same questions repeated monotonously every day is also not the best action to take because this will soon start to irritate the patient and that is why the robotic medical assistant will change the order and the frequency of the questions depending on how the patient respond. Therefore while asking some of the programmed questions about possible breathing problems or feeling tired, the robotic medical assistant will then proceed to ask psychological questions such as those relating to the mood of the patient or in general what the patient are doing. Some of these robotic medical assistants will even crack the occasional joke but then they are able to determine whether the patient likes those jokes or not and if not they will desist.

Driving change requires dedication. In the above example, it is clear that the medical sector is benefiting from those who are dedicated to an “AI first” approach – backed by the sort of R&D budget to support this.

 

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