Skin disease diagnosis using image analysis and natural language processing
This addresses healthcare accessibility issues for Zambians, but it appears incremental as it applies existing methods to a new domain without claiming specific performance gains.
The researchers tackled the shortage of medical staff in Zambia by implementing a deep learning model for skin disease diagnosis using image analysis and natural language processing, aiming to prove its capability for clinical diagnosis and reduce practitioner workload.
In Zambia, there is a serious shortage of medical staff where each practitioner attends to about 17000 patients in a given district while still, other patients travel over 10 km to access the basic medical services. In this research, we implement a deep learning model that can perform the clinical diagnosis process. The study will prove whether image analysis is capable of performing clinical diagnosis. It will also enable us to understand if we can use image analysis to lessen the workload on medical practitioners by delegating some tasks to an AI. The success of this study has the potential to increase the accessibility of medical services to Zambians, which is one of the national goals of Vision 2030.