Medical knowledge and healthcare information have dramatically expanded
in the past decades. The advents of medical ultra-subspecialty, mandated regulatory
agencies, and modern molecular techniques (–omics) have made the field of Medicine
spread in both depth and breadth. Medicine has become extremely complex beyond the
unaided human mind. Humans make majority of decisions using six or fewer data
points, otherwise, the human brain can become mentally exhausted. Artificial
intelligence (AI) has been designed to analyze seamlessly over thousands of data
points, including complex nonlinear interaction between data points. A novel
perspective of a future in medicine incorporates data-driven systems while AI and
clinicians work collaboratively in conditional automation, similar to the current state of
automatic vehicles. The role of human physicians may shift to back-up decision
making and diagnosis of rare diseases, rather than routine, repetitive works. Given the
expected growth in the field, physicians should be familiar with the opportunities and
limitations of AI and machine learning. This chapter will lay out the principle concepts
of artificial intelligence, machine learning and artificial neural networks and will
explore the recent studies and possible implications of AI in medical specialties.
Keywords: Artificial intelligent, Deep learning, Healthcare, Machine learning.
