**4. Synthesis and conclusion**

Similar to all other transformational human inventions, the emergence of AI/ML is a culmination of various simultaneous advances – often parallel and co-dependent – that synergistically combine to facilitate computational processes that approximate the "functional outcomes" of various human logical processes. Among the advances that were required for AI/ML to enter the mainstream were modern integrated circuits, higher computer processing speeds, greater amounts of computer memory, software engineering knowledge, and the ability to harness the power of the Internet to gather vast amounts of high-density data in a very efficient manner.

As the early, more rudimentary capabilities of AI/ML grew, so did the diversity of their applications. With further growth in hardware, software, and implementation infrastructure, increasingly complex areas (and problems) became amenable to AI's general "scope of abilities." This gradually expanded into highly sophisticated systems and areas, such as social sciences and healthcare. In this collection of chapters, we will discuss current trends and future developments related to artificial intelligence and machine learning across medical and surgical specialties.

*Introductory Chapter: Artificial Intelligence in Healthcare – Where Do We Go from Here? DOI: http://dx.doi.org/10.5772/intechopen.111823*
