The Lack of Rigor in AI Research, Beware of the Hype
This blog aims to build on Nada’s ophthalmology blog , raising awareness of the hype surrounding AI, and talks about the issue of health data poverty and why we need to address this. The lack of rigour in AI research, beware of the hype The literature within the AI healthcare field has grown considerably in the last three years. Several reviews have discussed current and future use-cases across healthcare, and NHSX have summarised these applications (see Figure 1) within their report: ‘Artificial Intelligence: How to get it right’ . Topol outlined how the benefits would be impactful at three levels: · Clinicians- primarily assisted by rapid diagnostic aid in patient management (particularly image interpretation e.g radiology, pathology, ophthalmology [as Nada discussed] ), and automation of repetitive administrative tasks to free up time. · Health systems- operational applications in non-patient facing, back-end systems that improve workflow, and a reduction in varia