Artificial intelligence-driven diagnosis of β-thalassemia minor & iron deficiency anemia using machine learning models.

IF 7.1 3区管理学 Q1 BUSINESS

Electronic Markets Pub Date : 2024-01-25 DOI:10.5937/jomb0-38779

Süheyl Uçucu, Fatih Azik

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引用次数: 0

Abstract

Background: Iron deficiency anemia (IDA) and b-thalassemia minor (BTM) are the two most common causes of microcytic anemia, and although these conditions do not share many symptoms, differential diagnosis by blood tests is a time-consuming and expensive process. CBC can be used to diagnose anemia, but without advanced techniques, it cannot differentiate between iron deficiency anemia and BTM. This makes the differential diagnosis of IDA and BTM costly, as it requires advanced techniques to differentiate between the two conditions. This study aims to develop a model to differentiate IDA from BTM using an automated machine-learning method using only CBC data.

Methods: This retrospective study included 396 individuals, consisting of 216 IDAs and 180 BTMs. The work was divided into three parts. The first section focused on the individual effects of hematological parameters on the differentiation of IDA and BTM. The second part discusses traditional methods and discriminant indices used in diagnosis. In the third section, models developed using artificial neural networks (ANN) and decision trees are analysed and compared with the methods used in the first two sections.

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机器学习模型可以预测血红蛋白变异的存在:基于人工神经网络的β-地中海贫血和缺铁性贫血的识别

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来源期刊

Electronic Markets Multiple-

CiteScore

14.80

自引率

15.30%

发文量

期刊介绍： Electronic Markets (EM) stands as a premier academic journal providing a dynamic platform for research into various forms of networked business. Recognizing the pivotal role of information and communication technology (ICT), EM delves into how ICT transforms the interactions between organizations and customers across diverse domains such as social networks, electronic commerce, supply chain management, and customer relationship management. Electronic markets, in essence, encompass the realms of networked business where multiple suppliers and customers engage in economic transactions within single or multiple tiers of economic value chains. This broad concept encompasses various forms, including allocation platforms with dynamic price discovery mechanisms, fostering atomistic relationships. Notable examples originate from financial markets (e.g., CBOT, XETRA) and energy markets (e.g., EEX, ICE). Join us in exploring the multifaceted landscape of electronic markets and their transformative impact on business interactions and dynamics.