Artificial intelligence supported anemia control system (AISACS) to prevent anemia in maintenance hemodialysis patients
Anemia, for which erythropoiesis-stimulating agents (ESAs) and iron supplements (ISs) are used as preventive measures, presents important difficulties for hemodialysis patients. Nevertheless, the number of physicians able to manage such medications appropriately is not keeping pace with the rapid increase of hemodialysis patients. Moreover, the high cost of ESAs imposes heavy burdens on medical insurance systems. An artificial-intelligence-supported anemia control system (AISACS) trained using administration direction data from experienced physicians has been developed by the authors. For the system, appropriate data selection and rectification techniques play important roles. Decision making related to ESAs poses a multi-class classification problem for which a two-step classification technique is introduced. Several validations have demonstrated that AISACS exhibits high performance with correct classification rates of 72-87% and clinically appropriate classification rates of 92-98%.
Code (0)
등록된 구현이 없습니다.
Tasks
ClassificationDecision MakingGeneral ClassificationMulti-class ClassificationSimilar Papers 제목 키워드 기반
Portable system for the prediction of anemia based on the ocular conjunctiva using Artificial Intelligence
Anemia is a major health burden worldwide. Examining the hemoglobin level of blood is an important way to achieve the diagnosis of anemia, but it requires blood drawing and a blood test. In this work we propose a non-inv…
AI-Driven anemia diagnosis: A review of advanced models and techniques
Anemia, a condition marked by insufficient levels of red blood cells or hemoglobin, remains a widespread health issue affecting millions of individuals globally. Accurate and timely diagnosis is essential for effective m…
Predicting Anemia Among Under-Five Children in Nepal Using Machine Learning and Deep Learning
Childhood anemia remains a major public health challenge in Nepal and is associated with impaired growth, cognition, and increased morbidity. Using World Health Organization hemoglobin thresholds, we defined anemia statu…
Binary ClassificationNovel Meta-Heuristic Model for Discrimination between Iron Deficiency Anemia and B-Thalassemia with CBC Indices Based on Dynamic Harmony Search
In recent decades, attention has been directed at anemia classification for various medical purposes, such as thalassemia screening and predicting iron deficiency anemia (IDA). In this study, a new method has been succes…
The Identification and Categorization of Anemia Through Artificial Neural Networks: A Comparative Analysis of Three Models
This paper presents different neural network-based classifier algorithms for diagnosing and classifying Anemia. The study compares these classifiers with established models such as Feed Forward Neural Network (FFNN), Elm…