In Seminars in diagnostic pathology
Machine learning (ML) is becoming an integral aspect of several domains in medicine. Yet, most pathologists and laboratory professionals remain unfamiliar with such tools and are unprepared for their inevitable integration. To bridge this knowledge gap, we present an overview of key elements within this emerging data science discipline. First, we will cover general, well-established concepts within ML, such as data type concepts, data preprocessing methods, and ML study design. We will describe common supervised and unsupervised learning algorithms and their associated common machine learning terms (provided within a comprehensive glossary of terms that are discussed within this review). Overall, this review will offer a broad overview of the key concepts and algorithms in machine learning, with a focus on pathology and laboratory medicine. The objective is to provide an updated useful reference for those new to this field or those who require a refresher.
Albahra Samer, Gorbett Tom, Robertson Scott, D’Aleo Giana, Kumar Sushasree Vasudevan Suseel, Ockunzzi Samuel, Lallo Daniel, Hu Bo, Rashidi Hooman H
2023-Feb-16
Artificial intelligence, Laboratory medicine, Learning, Machine learning, Pathology, Predictive modeling, Supervised
