Artificial intelligence (AI) has the potential to revolutionize healthcare by diagnosing diseases at scale and predicting future infectious diseases. The World Economic Forum (WEF) and US consulting firm ZS have published a study titled “Scaling intelligent solutions with AI in healthcare,” which highlights these possibilities. AI systems can also improve the quality of clinical studies, optimize site selection, recruit participants, and generate representative synthetic data. The report predicts that global health data will exceed 10 zettabytes by 2025. However, a survey revealed that over 70% of healthcare providers feel overwhelmed by the amount of patient data available to them, highlighting the need for powerful technology like AI. The COVID-19 pandemic has worsened existing issues in healthcare, including staffing shortages and strained health systems. AI offers a promise of doing more with less and reducing healthcare demand. The study involved analyzing more than 400 existing AI use cases and conducting interviews with leading companies in technology, healthcare, biopharmaceuticals, government, and academia. Deep learning, which involves training algorithms on large datasets, is one prominent AI technique. Examples of AI use in healthcare include Apollo Hospitals using AI to estimate cardiovascular risk and BlueDot using AI to detect and predict pandemics. Automating patient triage and symptom assessment is another area where AI can reduce the burden on healthcare workers. However, the adoption of AI in healthcare faces barriers such as insufficient high-quality data, low trust in AI solutions, and a lack of technological infrastructure. Integration with electronic health record systems and other healthcare platforms is necessary for AI tools to become more mainstream. Big-tech companies like Google have made progress in refining AI in healthcare to accommodate different languages, dialects, and cultures.
