Hematology

Latest AI and machine learning research in hematology for healthcare professionals.

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Showing 3601-3620 of 8,809 articles

Erythrogram directly from the microscope eyepiece: a feasibility study using artificial intelligence

Erythrocyte indices are essential for the diagnosis and monitoring of hematologic diseases, but their determination depends on automated hematology analyzers, which limits access in regions with limited laboratory infrastructure. Although artificial intelligence approaches have been proposed for hematologic analysis, they usually rely on slide scanners or digitization systems. To date, no validate...

Predicting the efficacy of Recombinant Human Thrombopoietin in Treating Cancer Therapy-Related Thrombocytopenia:based on stacking ensemble methods

The project aimed to develop a data-driven approach for predicting platelet recovery in cancer treatment–induced thrombocytopenia (CTIT) patients receiving recombinant human thrombopoietin (Rh-TPO). By integrating key clinical indicators into a predictive modeling framework, the study sought to enhance understanding of individual treatment responses and facilitate timely clinical decision-making. ...

A method for lung cancer detection and staging from a drop of blood plasma via Raman spectroscopy of well-based samples (ROWS)

We present a new method for lung pathology detection in blood plasma, including lung cancer staging. Raman spectroscopy uses inelastically scattered l...

Early Detection of Cardiovascular Disease Risk Using Multi-Parameter Biomarker Analysis and Machine Learning: A Prospective Cohort Study

Cardiovascular disease (CVD) remains the leading cause of mortality globally, with many events occurring in individuals without prior diagnosed condit...

Nationwide Spatiotemporal Dynamics and Machine Learning Prediction of Anemia Among Women in Lesotho, 2023–2024

Despite substantial efforts, anemia continues to pose a significant public health challenge, disproportionately affecting women of reproductive age. I...

Machine Learning-Based Identification of Blood Biomarkers that Distinguish Precachectic and Cachectic Patients with Pancreatic Ductal Adenocarcinoma

Identification of minimally invasive biomarkers of different stages of cachexia (Ca), and precachexia (PCa) in particular, might help clinicians in tr...

Temporal deep learning with clinically engineered biomarkers for the early prediction of type 2 diabetes

Diabetes mellitus remains a major global health burden, causing an estimated 3.4 million deaths in 2024 and highlighting the need for accurate early i...

Data-augmented machine learning redefines the effective concentration of eculizumab in complement blood disorders

Eculizumab, a humanized monoclonal antibody targeting the complement lytic pathway protein C5, has demonstrated high efficacy in the treatment of paro...

Multi-domain Identification of Myocardial Infarction Incidence using Explainable AI: The Overlooked Role of Periodontal Health

Myocardial infarction (MI) is a major global health concern influenced by diverse risk factors. Despite growing evidence of oral– systemic connections...

A Novel Approach using CapsNet and Deep Belief Network for Detection and Identification of Oral Leukopenia

Oral cancer constitutes a significant global health concern, resulting in 277,484 fatalities in 2023, with the highest prevalence observed in low- a...

Construction of a predictive model for rebleeding risk in upper gastrointestinal bleeding patients based on clinical indicators such as infection.

BACKGROUND: The annual incidence of upper gastrointestinal hemorrhage (UGIB) is about 60 cases/100,000 people, and about 40% of UGIB patients have hem...

Jan 1 2025 40438212
Identification of hub immune-related genes and construction of predictive models for systemic lupus erythematosus by bioinformatics combined with machine learning.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that involves multiple systems. SLE is characterized by the production of autoantib...

Jan 1 2025 40438384
Machine Learning-Based Prediction of In-Hospital Mortality in Severe COVID-19 Patients Using Hematological Markers.

The mortality rate is very high in patients with severe COVID-19. Nearly 32% of COVID-19 patients are critically ill, with mortality rates ranging fr...

Jan 1 2025 40391097
Significance and mechanisms of perineural invasion in malignant tumors.

Cancer remains the second leading cause of death worldwide. Tumor invasion and metastasis pose significant challenges for clinical management. In addi...

Jan 1 2025 40421086
Association of early enoxaparin prophylactic anticoagulation with ICU mortality in critically ill patients with chronic obstructive pulmonary disease: a machine learning-based retrospective cohort study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a major contributor to global morbidity and mortality, particularly during acute exacerbat...

Jan 1 2025 40421211
Recent progress in tuberculosis diagnosis: insights into blood-based biomarkers and emerging technologies.

Tuberculosis (TB) remains a global health challenge, with timely and accurate diagnosis being critical for effective disease management and control. R...

Jan 1 2025 40406513
An efficient leukemia prediction method using machine learning and deep learning with selected features.

Leukemia is a serious problem affecting both children and adults, leading to death if left untreated. Leukemia is a kind of blood cancer described by ...

Jan 1 2025 40378164
An in vitro and machine learning framework for quantifying serum albumin binding of per- and polyfluoroalkyl substances.

Per- and polyfluoroalkyl substances (PFAS) are a diverse class of anthropogenic chemicals; many are persistent, bioaccumulative, and mobile in the env...

Jan 1 2025 39298512
Deep learning based semantic segmentation of leukemia effected white blood cell.

Medical image segmentation has numerous applications in diagnosing different diseases. Various types of diseases are found in white blood and Red bloo...

Jan 1 2025 40338981
Artificial intelligence model for perigastric blood vessel recognition during laparoscopic radical gastrectomy with D2 lymphadenectomy in locally advanced gastric cancer.

BACKGROUND: Radical gastrectomy with D2 lymphadenectomy is standard surgical protocol for locally advanced gastric cancer. The surgical experience and...

Dec 30 2024 39963943
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