Hematology

Omics-based computational approaches for biomarker identification, prediction, and treatment of Long COVID.

Long COVID, or post-acute sequelae of COVID-19 (PASC), is a major global health problem, with cumulative estimates suggesting that around 400 million people worldwide have been affected. It is characterized by persistent or new symptoms such as fatigue, cognitive impairment, and breathlessness lasting beyond four weeks after acute infection. Diverse clinical manifestations, chronic course, and inc...

Machine learning-based binary classification of elevated HbA1c (≥6.5 %) for risk assessment.

OBJECTIVE: One of the most important biomarkers for evaluating long-term glycemic management and estimating the risk of diabetes is glycated hemoglobin (HbA1c). Early risk assessment and intervention techniques can be improved by identifying important clinical and demographic variables. Through the integration of clinical indicators (lipid profiles, albumin, and liver enzymes) and demographic char...

DGPCNet: anemia detection from multimodal palm, fingernails, and eye conjunctiva images using deep global pyramid convolutional network.

BACKGROUND: Anemia is one of the most common hematological disorders causing fatigue, increased vulnerability to infection, low birth weight, and thre...

Development and multicenter validation of a machine learning model for postoperative sepsis risk in critically Ill traumatic spinal injury patients.

OBJECTIVE: To develop and validate a machine learning model for postoperative sepsis in critically ill traumatic spinal injury (TSI) patients, a frequ...

Advancements in the study of exosomes in disease diagnosis and treatment.

Exosomes are small, membrane-enclosed vesicles that can originate from a variety of sources and contain a wealth of material. They are involved in phy...

Artificial intelligence-driven 3-dimensional simulation system for enhanced preoperative planning in gastric cancer surgery: a retrospective validation study.

BACKGROUND: Few studies have developed artificial intelligence (AI) systems for the automatic recognition of the anatomy of the stomach, a dynamic org...

In vitro blood flow dataset in circular microchannels: High-speed videomicroscopy, micro-piv, and cell-free layer measurements.

This dataset provides micro-particle image velocimetry (µPIV) and high-speed imaging of red blood cell (RBC) suspensions flowing through circular glas...

Multilayer Ag-Au-BP-TIBr-FASnI3 Kretschmann surface plasmon resonance biosensor for high sensitivity refractive index analysis: A computational and machine learning approach.

Detection of refractive-index variations is fundamental for the development of next-generation optical sensing platforms capable of supporting future ...

Cross-modality fusion of hematology-based digital and molecular biomarkers for intelligent epidemiological screening and surveillance of hepatocellular carcinoma.

Early detection of hepatocellular carcinoma (HCC) remains a critical challenge due to the disease's complexity and the limitations of current screenin...

The Application of Machine-Learning Algorithms for Multiclass Classification of Microcytic Anemia Revealed That a Minimum Required Number of Hematological Parameters Is Enough to Achieve High Diagnostic Accuracy.

INTRODUCTION: Thalassemia is a major global health concern, as declared by the World Health Organization (WHO). Accurate screening of heterozygotes is...

Discovery of hemostatic component combination from Nelumbinis Receptaculum using dual machine learning spectrum-effect analysis.

ETHNOPHARMACOLOGICAL RELEVANCE: Nelumbinis Receptaculum (NR) were hemostatic herbal medicines for treating metrorrhagia, hematuria or hemorrhoids in e...

Diabetes-linked metabolic dysfunction relates with distinct tau phosphorylation patterns, neuroinflammation and cognitive impairment in mouse models of Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by amyloid-β plaques and tau neurofibrillary tangles, with tau path...

Personalized adrenal gland volume reference ranges and development of a fully automated deep learning screening tool.

OBJECTIVE: This study aims to develop a low-dose CT-based, fully automated deep learning tool for screening adrenal gland volume abnormalities and est...

Development and validation of a novel orthopedic blood use prediction model incorporating lab tests and thromboelastography.

OBJECTIVE: To develop and validate a prediction model integrating laboratory parameters and thromboelastography (TEG) for forecasting blood transfusio...

Development of Artificial Intelligence for Quantitative Assessment of Nasal Inflammatory Cytology in Chronic Rhinitis by Whole-Slide Images.

BACKGROUND: Chronic rhinitis (CR) is currently recognized as a syndrome that manifests in different phenotypes. We aimed to establish an artificial in...

Emerging risk factors for stroke and bleeding in patients with atrial fibrillation and heart failure-a narrative review.

Atrial fibrillation (AF) and heart failure (HF) frequently coexist, which leads to adverse clinical outcomes and a significant increase in the risk of...

Diagnosis of head and neck cancer by AI-based tumor-educated platelet RNA profiling of liquid biopsies.

Over 95% of head and neck cancers are squamous cell carcinoma (HNSCC). HNSCC is mostly diagnosed late, causing a poor prognosis despite the applicatio...

ICSH Recommendations for Monocyte Cell Lineage Morphologic Identification, Nomenclature Harmonization, and Utilization as a Biomarker.

Monocytes are key components of the Mononuclear Phagocyte System, crucial in immune defense, inflammation, and tissue repair. Accurate identification ...

Blast cell segmentation and leukemia classification using hybrid Deep Kronecker WideResNet using blood smear images.

Acute Lymphoblastic Leukemia (ALL) is a dangerous form of leukemia, which disturbs the bone marrow and irregular White Blood Cells (WBC) for the perso...

Interpretable machine learning model based on blood parameters for screening high myopia.

OBJECTIVE: To develop an interpretable machine learning (ML) model using routine blood parameters for high myopia (HM) screening as a convenient and c...