Artificial Intelligence Healthcare

1774 Words4 Pages

Team 8
Artificial Intelligence – Medical & Healthcare Industry

Introduction / Relevance
The increasing cost of healthcare and a growing number of complex medical issues has highlighted a number of inefficiencies within the healthcare system. Artificial intelligence (AI) may be an answer to these growing concerns. Increasing rates of drug-resistant and hospital-acquired infections, misdiagnosis of patients, and ineffective preventative medicine could all be greatly reduced using AI systems. In addition, AI could help to reduce failures in care delivery. It is common for hospitals to be exposed to these issues and financial records show that they have a negative impact in terms of cost. Furthermore, the mandatory use of electronic health records …show more content…

It can standardize processes and aggregate data in a way that allows it to be used for preventative medicine. The potential for this technology within the healthcare industry is immeasurable. As AI and cognitive computing mature further over the next few years, they will become key competitive differentiators for healthcare institutions. It is likely that without implementation of one or more AI-based systems, that our hospital will no longer be a facility of choice in the area.
Lowering costs and improving the delivery of effective care we provide to our patients is paramount. This report will outline technologies that we believe will provide the greatest return on investment for our hospital in both the short and long term. We will show the opportunities that AI technology will allow us to take advantage of, and the key challenges we are likely to face in implementing them. …show more content…

Running such systems requires operational expenditure for maintenance and licensing fees. Further operational spending will also be required in order to train staff and potentially to recruit additional IT staff to operate and maintain the system. Moreover, many AI systems are still in the early stages of development therefore the technology is niche. This allows vendors and consultants to charge high prices.

Data integration: Successful implementation of AI systems requires the integration of data from disparate and discrete sources. Data sources can include EHRs, medical journals or books, national statistics and even data from patients’ personal health tracking devices. The integration process requires significant time with data integration specialists to design, configure, test and implement the associated hardware and software. In addition, new data sources occasionally need to be integrated to refine and improve the systems. As such is it necessary to budget for the services of data specialists on a period

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