Artificial Intelligence Studies and Data Analysis in Chronic Lymphocytic Leukemia: A Current Review

ABSTRACT
Artificial intelligence (AI) is characterized as a knowledge project that views knowledge as an object, draws conclusions from it, investigates and evaluates the forms that knowledge takes, and then uses these techniques to mimic human thought processes. Certain subfields of AI, such as machine learning and deep learning, bear a strong resemblance to medical specializations. The main driver of progress in this field is the ability of deep learning algorithms, or artificial neural networks with multiple processing layers, to simulate intricate nonlinear input-output interactions and to identify patterns and extract features from low-level data representations. AI in hematology has made dramatic progress in recent years. However, much of this progress is seemingly scattered and lacks a coherent structure that is difficult for a hematologist to follow. Chronic lymphocytic leukemia (CLL) is a special type of hematological cancer that occurs in older ages. Uncontrolled and gradual proliferation of monoclonal B cells in the blood, bone marrow, spleen and lymph nodes is responsible for the pathogenesis of the disease. Patients with CLL have extremely variable clinical courses, and overall survival times can range from several months to decades. Thirty percent of patients never need medical treatment. Given the extreme heterogeneity of CLL, the development of new prognostic models is inevitable. Presently, there is a growing body of research demonstrating the effectiveness of AI-based models in diagnosing and determining the prognosis of CLL. In this article, we will present an up-to-date review of AI in hematology, with a special focus on the radiology, pathology, genetics, diagnostic, therapeutic applications of AI from an AI perspective in the diagnosis of CLL, a specialized cancer of hematology that appears in advanced age. We will discuss a selection of selected papers demonstrating the current state-of-the-art use of AI in CLL and its potential future uses.
Keywords: Chronic lymphocytic leukemia, machine learning, diagnosis, artificial intelligence