Uses of AI in Healthcare

1. Uses of AI in Healthcare Artificial Intelligence (AI) until today is a dicey affair for people. This is because people are sceptical about letting AI handle their own personal data, on the contrary, they find AI to be more dependable when it comes to healthcare. AI in healthcare is said to provide better, accurate, and precise information and medical treatment. AI for Application Monitoring in healthcare is not just beneficial for patients, it is also of major importance to the healthcare companies. AI and healthcare can function together and give value only if the interconnection between is inter-operable and smooth. Here are some of the ways Artificial Intelligence (AI) can affect the areas and technologies of the healthcare industry: Brain-Computer Interfaces (BCI) that are backed by Artificial Intelligence (AI), helps the patients to restore their fundamental expressions of movement, speech and meaningful interaction with people and the environment which a patient loses because of some kind of trauma or neurological diseases. Artificial Intelligence will enable the next generation radiology tools with even more details and accuracy. So much that, it will be able to replace the need for samples in some cases. AI is also enabling “virtual biopsies”. This will bring advancement in the field of radiomics. AI cloud helps to lessen the shortages of trained healthcare providers. This includes radiologists and ultrasound technicians. AI helps to overcome the severe deficit of qualified clinical staffs. Electronic Health Records (EHR’s) play a major role in the journey of the healthcare industry towards digitization. EHR’s come with endless documentations, cognitive load and user burnout. AI is being used by EHR developers to create a more intuitive interface as well as automate the routine processes that take up the user’s time unnecessarily. 1

2. Patient deterioration and or the development of complications can be detected by smart devices which are AI-based. This early detection helps reduce the outcomes as well as save cost. AI and Machine Learning algorithms ability to synthesize highly complex datasets helps to identify cancer patients who require immunotherapy, which is the best treatment in this case. AI assimilates the data which are related to health and is generated through personal devices and wearables for extracting actionable insights and better monitoring. Clinical quality imaging can be supplemented by smartphone devices which use built-in AI hardware and software which has the ability to collect images of skin lesions, eyes, wounds, medications, infections, and other important subjects. Ophthalmology and dermatology are early beneficiaries of this trend. AI can be used for risk scoring and clinical decision support. It can also be used as early alerting of the most promising areas of development. The ones who are undertrained are allowed by AI to go through simulations which are naturalistic in a way which cannot be done by simple computer-driven algorithms. The above article has been sourced Zero Incident Framework (ZIF), who provides real-time user monitoring tools and the best AIOps solutions in USA. 2