Informational and Analytical System to Diagnose Anemia

Uvaliyeva, Indira; Belginova, Saule; Ismukhamedova, Aigerim

doi:10.1145/3234698.3234716

Cited by 12 publications

(3 citation statements)

References 14 publications

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“…In today's scenarios many healthcare decisions are being taken by predictive modeling and machine learning techniques [5]. Medical information systems, in fact, represent a complex monitoring system that takes into account various aspects, criteria and management goals, which contributes to improving the efficiency of management of distributed facilities.…”

Section: Methods 31 Literature Reviewmentioning

confidence: 99%

Research and implementation of the medical text analysis algorithm for predicting mortality

Rakhmetullina,

Belginova,

Karlygash

et al. 2024

IJEECS

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Mortality prediction has a role to play in the development of a descriptive measure of the quality of care that provides a fair and equitable means of comparing and evaluating hospitals. This article describes a study of a medical text analysis algorithm for mortality prediction that used big data in the form of unstructured medical notes. The article describes the concept of using text mining technology for medical systems, a method for preprocessing medical data to predict patient mortality, an algorithm for predicting patient deaths based on the logistic regression classifier and presents a software module for implementing the proposed algorithm.

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Section: Methods 31 Literature Reviewmentioning

confidence: 99%

Research and implementation of the medical text analysis algorithm for predicting mortality

Rakhmetullina,

Belginova,

Karlygash

et al. 2024

IJEECS

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“…This involves reducing the data dimensionality through feature selection or identifying the most significant attributes for analysis. Data preprocessing is a critical stage in data analytics and machine learning, encompassing a series of operations to cleanse and convert raw data for analytical purposes [27]. The pre-processing of loaded data incorporates the following procedures:…”

Section: Designing a Database And Web Application Based On A Rule Basementioning

confidence: 99%

Implementation of a Base of Rules for Differential Diagnosis of Clinical and Hematological Syndromes Based on Morphological Classification Algorithm

Uvaliуeva,

Ismukhamedova,

Belginova

et al. 2024

sjaitu

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The evolving landscape of modern medicine underscores the growing importance of automating diagnostic processes. This advancement is not merely a convenience but a necessity to harness the full potential of technological progress, aiming to elevate research and clinical outcomes to new heights. Among the innovative strides in this field, the development of diagnostic systems based on morphological classification algorithms stands out. Such systems, rooted in comprehensive rule bases for differential diagnosis, promise to revolutionize the way we approach complex medical conditions. This paper introduces a cutting-edge system that epitomizes this evolution. Designed to harness the power of data analysis, it paves the way for groundbreaking research opportunities. At the heart of this system is a sophisticated set of rules derived from a morphological classification algorithm. This foundation enables the system to perform automated diagnoses of a wide array of clinical and hematological syndromes with unprecedented accuracy. A notable application of this technology is its ability to diagnose anemia by analyzing six distinct blood parameters and further categorize the anemia type based on biochemical criteria. The implications of such diagnostic capabilities are profound. By enabling the systematic collection and analysis of statistical data, the system facilitates in-depth research into the prevalence of diseases across different demographic groups. It aids in identifying disease patterns and supports preventive medicine efforts, potentially shifting the paradigm from treatment to prevention. This study not only highlights the system's capacity for enhancing diagnostic precision but also emphasizes its role as a catalyst for medical research and the improvement of healthcare delivery. The integration of such technologies into the medical field promises to enhance the quality of care, streamline diagnostic processes, and open new avenues for medical research, ultimately contributing to the advancement of global health standards.

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“…The incidence rate of anemia in 2019 was reported to be 31.8% of the total number of pregnant women in the Republic of Kazakhstan, and 30.8% in Aktobe city, where half of the cases were caused by iron deficiency anemia (IDA) – 1,716.3 per 100,000 of the population [9]. The national studies in Kazakhstan estimated the IDA incidence within 36.0% [10]. The screening studies in Almaty showed that anemia occurs in 23.2% of cases in women at the age of 18–49 years.…”

Section: Introductionmentioning

confidence: 99%

Diagnostic Relevance of Ferrokinetic Laboratory Markers in Anemic Pregnant Women

Aringazina¹,

Zharmakhanova²,

Курманалина³

et al. 2020

Gynecol Obstet Invest

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Objectives: Different forms of anemia are considered as the most frequent complication of the gestational period. By its etiology, pathogenesis, and clinical hematology, it is not a single disease. Among all forms of anemia occurring during pregnancy, iron deficiency anemia (IDA) is the most common, accounting for 80-95% of all cases. Design: The article describes a theoretical basis for the diagnosis of the anemic syndrome among pregnant women, the determining factors of its development, and the diagnostic methods at different gestational periods. Participants/Materials, Setting, and Methods: Diagnostic and prognostic values of iron balance indicators in the body were established for IDA during pregnancy to improve the outcome of childbirth. A total of 140 anemic patients were examined. The control group consisted of 50 pregnant women without anemia and other significant health problems, 48 IDA pregnant women, and 42 pregnant women with anemia caused by various chronic diseases, including rheumatoid arthritis. All patients of the main and control groups were registered on clinical records at the Family Planning Center in Aktobe city, Kazakhstan. Results: Ferrokinetic indicators were suggested for diagnosing IDA and anemia of chronic diseases. It was established that IDA is characterized by low ferritin levels during gestation, while increased ferritin and C-reactive protein are typical for anemia of chronic diseases. Limitations: Differential diagnostics was applied for pregnant women with IDA and anemia of chronic diseases to observe the dynamics of serum ferritin and C-reactive protein (CRP) levels at different gestational periods. The article presents the results of a study on ferrokinetics in pregnant women with IDA and anemia caused by inflammation or chronic diseases. Other causes of anemia leading to a decrease in hemoglobin (Hb) levels to <90 g/L include hemoglobinopathies, which were not considered in this study. Conclusions: Determination of iron deficiency in pregnant women at different gestational periods will allow for identifying the risk group of anemic patients and deciding on the treatment. IDA (Hb <100 g/L) can be effectively measured by ferritin level <15 ng/mL, iron level of <11.5 μmol/L, and transferrin level >2.6 mg/L at p < 0.001. Anemia due to chronic diseases (Hb <100 g/L) can be effectively diagnosed with ferritin above 15 μg/L and CRP above 10 mg/L at p < 0.001.

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Informational and Analytical System to Diagnose Anemia

Cited by 12 publications

References 14 publications

Research and implementation of the medical text analysis algorithm for predicting mortality

Research and implementation of the medical text analysis algorithm for predicting mortality

Implementation of a Base of Rules for Differential Diagnosis of Clinical and Hematological Syndromes Based on Morphological Classification Algorithm

Diagnostic Relevance of Ferrokinetic Laboratory Markers in Anemic Pregnant Women

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