ABSTRACT
This chapter first defines the terms and the intricate relations among machine learning, big data, and artificial intelligence. The availability of powerful computational tools to reduce extremely large digitized datasets (big data) through regularization contributes to major advances in machine learning, which is a key component of artificial intelligence. The use of artificial intelligence in medicine is made possible with the major push towards digitizing medical records. The tradeoffs between sensitivity and specificity are discussed within the context of the overfitting process to extract meaningful and relevant values from big data. The concept of trainable neural networks is introduced as a key step in applying artificial intelligence in medicine. Examples are provided in the uses of artificial intelligence in classifying skin cancer, diagnosing diabetic retinopathy, identifying cardiovascular risk, and screening for breast cancer. The chapter concludes with a discussion on regulatory and ethical issues associated with the use of artificial intelligence in medicine.
