Hematologic cancer diagnosis and classification using machine and deep learning: State-of-the-art techniques and emerging research directives.

Hematology is the study of diagnosis and treatment options for blood diseases, including cancer. Cancer is considered one of the deadliest diseases across all age categories. Diagnosing such a deadly disease at the initial stage is essential to cure the disease. Hematologists and pathologists rely on microscopic evaluation of blood or bone marrow smear images to diagnose blood-related ailments. The abundance of overlapping cells, cells of varying densities among platelets, non-illumination levels, and the amount of red and white blood cells make it more difficult to diagnose illness using blood cell images. Pathologists are required to put more effort into the traditional, time-consuming system. Nowadays, it becomes possible with machine learning and deep learning techniques, to automate the diagnostic processes, categorize microscopic blood cells, and improve the accuracy of the procedure and its speed as the models developed using these methods may guide an assisting tool. In this article, we have acquired, analyzed, scrutinized, and finally selected around 57 research papers from various machine learning and deep learning methodologies that have been employed in the diagnosis of leukemia and its classification over the past 20 years, which have been published between the years 2003 and 2023 by PubMed, IEEE, Science Direct, Google Scholar and other pertinent sources. Our primary emphasis is on evaluating the advantages and limitations of analogous research endeavors to provide a concise and valuable research directive that can be of significant utility to fellow researchers in the field.

Chronic Oro-Genital Ulcerations as a Presenting Feature of Chronic Eosinophilic Leukemia: A Case Report.

Hypereosinophilia can be primary, including idiopathic hypereosinophilic syndrome (HES) and chronic eosinophilic leukemia, or secondary/reactive to various infective and non-infective stimuli. Chronic oro-genital ulcerations can occur due to various dermatological and non-dermatological disorders, and many times it serves as a useful indicator of an underlying systemic disorder. Hence, a case presenting with chronic oro-genital ulcerations needs a thorough evaluation. We are reporting an interesting case of a middle-aged male who had chronic oro-genital ulcerations as a presenting feature of chronic eosinophilic leukemia with FIP1L1-PDGFRA fusion (FIP1-like 1/platelet-derived growth factor receptor alpha). The patient's oro-genital ulcerations responded excellently to imatinib.