AIMC Topic: Anemia
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A novel method to predict the haemoglobin concentration after kidney transplantation based on machine learning: prediction model establishment and method optimization.
BMC medical informatics and decision making
Jul 8, 2025
BACKGROUND: Anaemia is a common complication after kidney transplantation, and the haemoglobin concentration is one of the main criteria for identifying anaemia. Moreover, artificial intelligence methods have developed rapidly in recent years, are wi...
Optimizing machine learning models for predicting anemia among under-five children in Ethiopia: insights from Ethiopian demographic and health survey data.
BMC pediatrics
Apr 22, 2025
BACKGROUND: Healthcare practitioners require a robust predictive system to accurately diagnose diseases, especially in young children with conditions such as anemia. Delays in diagnosis and treatment can have severe consequences, potentially leading ...
Shengxuebao Mixture improves carboplatin-induced anemia by inhibiting apoptosis and ferroptosis.
Journal of ethnopharmacology
Apr 2, 2025
ETHNOPHARMACOLOGICAL RELEVANCE: Shengxuebao Mixture (SXB) is a traditional Chinese medicine which has been widely used on treating Chemotherapy-induced leukopenia and multiple anemia. It remains unclear whether SXB has a role in chemotherapeutic-indu...
Assessment of anemia recovery using peripheral blood smears by deep semi-supervised learning.
Annals of hematology
Feb 21, 2025
Monitoring anemia recovery is crucial for clinical intervention. Morphological assessment of red blood cells (RBCs) with peripheral blood smears (PBSs) provides additional information beyond routine blood tests. However, the PBS test is labor-intensi...
Preoperative anemia is an unsuspecting driver of machine learning prediction of adverse outcomes after lumbar spinal fusion.
The spine journal : official journal of the North American Spine Society
Jan 30, 2025
BACKGROUND CONTEXT: Preoperative risk assessment remains a challenge in spinal fusion operations. Predictive modeling provides data-driven estimates of postsurgical outcomes, guiding clinical decisions and improving patient care. Moreover, automated ...
An explainable and supervised machine learning model for prediction of red blood cell transfusion in patients during hip fracture surgery.
BMC anesthesiology
Dec 19, 2024
AIM: The study aimed to develop a predictive model with machine learning (ML) algorithm, to predict and manage the need for red blood cell (RBC) transfusion during hip fracture surgery.
Leveraging machine learning models for anemia severity detection among pregnant women following ANC: Ethiopian context.
BMC public health
Dec 18, 2024
BACKGROUND: Anemia during pregnancy is a significant public health concern, particularly in resource-limited settings. Machine learning (ML) offers promising avenues for improved anemia detection and management. This study investigates the potential ...
Optimizing anemia management using artificial intelligence for patients undergoing hemodialysis.
Scientific reports
Nov 5, 2024
Patients with end-stage kidney disease (ESKD) frequently experience anemia, and maintaining hemoglobin (Hb) levels within a targeted range using erythropoiesis-stimulating agents (ESAs) is challenging. This study introduces a gated recurrent unit-att...
Deep Reinforcement Learning for personalized diagnostic decision pathways using Electronic Health Records: A comparative study on anemia and Systemic Lupus Erythematosus.
Artificial intelligence in medicine
Oct 2, 2024
BACKGROUND: Clinical diagnoses are typically made by following a series of steps recommended by guidelines that are authored by colleges of experts. Accordingly, guidelines play a crucial role in rationalizing clinical decisions. However, they suffer...
Predicting malnutrition-based anemia in geriatric patients using machine learning methods.
Journal of evaluation in clinical practice
Sep 23, 2024
BACKGROUND: Anemia due to malnutrition may develop as a result of iron, folate and vitamin B12 deficiencies. This situation poses a higher risk of morbidity and mortality in the geriatric population than in other age groups. Therefore, early diagnosi...
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