AI Significantly Scripting the Future of Healthcare

By CIOReview | Tuesday, November 7, 2017
229
425
95

Over a decade, there is a rise in artificial intelligence (AI) technologies in the healthcare realm. The development of AI applications in the delivery of care will however not dislodge the human relationships lays its grounds to enhance the efficiency and effectiveness of patient care. With the vast amounts of data revolving around healthcare, AI applications with their data mining, machine learning and data analytics processes, helps in assisting doctors and health care providers in faster, more accurate diagnosis and treatment.

It is been predicted that the health care market for AI is increasing at a 40 percent growth rate and is likely to arrive at $6.6 billion over the next few years. AI’s phenomenal growth is honed by transformation in health care delivery models, timelines and reimbursements. These revolutionary changes are in a way forcing biomedical technology companies to design AI applications to aid health care systems advance in patient care whilst reducing costs.

To highlight a little, one of the first AI applications in health care that came into practice was centered on reading CT, X-ray and other medical imaging scans for more precise diagnoses. AI is perfect for streamlining recurring work processes and administering vast amounts of data. Combining AI applications with that of the expertise of qualified clinicians, patient care in all the medical disciplines can be improved through the delivery of faster, more precise reports and treatment plans with availing instant data search and analysis processes for drug research. These AI applications are combined with patients’ biological data to predict the effectiveness of drug therapies amongst particular populations with greater precision in a more meaningful way.

The medical experts predicts that AI will have an instrumental footprint across the continuum of health care in areas such as patient engagement, chronic disease management, clinical decision making, financial modeling, and population health management.