Pattern Recognition of Acute Lymphoblastic Leukemia (ALL) Using Computational Deep Learning
نویسندگان
چکیده
Leukemia is a cancer of blood-producing cells, including the bone marrow. Abnormal white blood cells travel through vessels and multiply rapidly. Healthy in body become minority, imbalance increases chances infection body. or most common children ages 2 - 14. Most leukemia treated. Acute lymphocytic (ALL) type It progresses rapidly when immature are formed instead mature ones. Treatments for acute include drugs transfusions directly into veins, chemotherapy, all transplantation, which involve transferring organs tissues within from one person to another. In this paper, Pattern Recognition Lymphoblastic has been proposed using Computational Deep Learning. recognition technology uses mathematical algorithms identify patterns large datasets data. Analyzing data, can indicative certain states conditions. case ALL, algorithm would look cell count data that indicate presence ALL. These may changes number over time, composition levels proteins gene expressions associated with The ALLDM model achieved 81.53% (DDS) 87.92% (SDS) chemotherapy management, 79.16% 94.31% Stem Cell Transplantation Management, 63.77% 87.37% Radiation therapy Management 88.92% 85.86% Targeted management.
منابع مشابه
Cost-analysis of Treatment of Pediatrics Acute Lymphoblastic Leukemia based on ALL-BFM Protocol
Background Among all pediatric cancers acute lymphoblastic leukemia (ALL) is highly prevalent, butthe overall cost of ALL management is not well-known, there is a need to assess the Berlin-Frankfurt-Munster (BFM) protocol commonly used in ALL management in Iran. So, the aim of this study was to estimate direct and indirect costs of ALL treatment among children based on the ALL-BFM protocol from...
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2023
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2023.3260065