AI promises to be a boon to medical practice, improving diagnoses, personalizing treatment, and spotting future public-health threats. By 2024, experts predict, healthcare AI will be a nearly $20 billion market, with tools that transcribe medical records, assist surgery, and investigate insurance claims for fraud. Even so, the technology raises some knotty ethical questions. What happens when an AI system makes the wrong decision--and who is responsible if it does? How can clinicians verify, or even understand, what comes out of an AI "black box"?
Imagine there was a simple test to see whether you were developing Alzheimer's disease. You would look at a picture and describe it, software would assess the way you spoke, and based on your answer, tell you whether or not you had early-stage Alzheimer's. It would be quick, easy, and over 90% accurate--except for you, it doesn't work. That might be because you're from Africa. Imagine most of the world is getting healthier because of some new technology, but you're getting left behind.
Healthcare is undoubtedly one of the most crucial sectors for any nation, and obviously a matter for governmental and the private sector's focus. The healthcare system is tasked to ensure that society stays healthy at a reasonable expense. The way healthcare organisations are managed impacts the professional growth and satisfaction of doctors, nurses, counsellors and other healthcare professionals. Yet healthcare is often under resourced; can innovations within the industry reduce costs and improve outcomes? Emerging technology is completely transforming the business models of hospitals and health providers, changing the work of care professionals forever.
Is Artificial Intelligence (AI) the silver bullet that will make doctors all over the world unemployed? Will AI be able to outperform oncologist in creating treatment plans for cancer patients? Keep reading and get new perspectives on healthcare AI as I untangle opportunities and grand challenges within the field. "Too much information, too little time" is one of the big challenges in healthcare today. Patients, healthcare professionals and medical devices generate huge amounts of data.