I once worked on a medical hackathon concept for computer-assisted population screening for cervical cancer in a developing nation. Community health workers take photos. The AI would look at the images, and make a call of "clearly negative" vs "clearly positive" vs "needs (scarce) expert review". But taking good photos is hard, so it's also "photos insufficient" and "worker needs additional mentorship on taking photos". Only by computes reducing all three costs - expert workload, exam success, and quality-control/training - might successful deployment be financially and logistically plausible for that nation.