Hematology

Validation of an AI-enabled exome/transcriptome liquid biopsy platform for early detection, MRD, disease monitoring, and therapy selection for solid tumors.

Effective clinical management of patients with cancer requires highly accurate diagnosis, precise therapy selection, and highly sensitive monitoring of disease burden. Caris Assure is a multifunctional blood-based assay that couples whole exome and whole transcriptome sequencing on plasma and leukocytes with advanced machine learning techniques to satisfy all three clinical testing needs on one pl...

Unstained Blood Smear Analysis: A Review of Rule-Based, Machine Learning, and Deep Learning Techniques.

Blood cells are central to oxygen transport, immune defense, and hemostasis. Their number and morphology act as sensitive biomarkers, making accurate segmentation and classification essential for hematological diagnostics. Biophotonic techniques now provide label-free imaging of unstained smears by exploiting intrinsic phase and scattering contrast, yet such images exhibit low optical signal and s...

Machine-Learning Prediction of Bleeding After Endoscopic Submucosal Dissection for Early Gastric Cancer: A Multicenter Study.

BACKGROUND: Endoscopic submucosal dissection (ESD) is a minimally invasive treatment for early gastric cancer (GC); however, post-ESD bleeding remains...

Deep learning predicts onset acceleration of 38 age-associated diseases from blood and body composition biomarkers in the UK Biobank.

A major challenge in multimorbid aging is understanding how diseases co-occur and identifying high-risk groups for accelerated disease development, bu...

Machine learning for the prediction of spontaneous preterm birth using early second and third trimester maternal blood gene expression: A cautionary tale.

Spontaneous preterm birth (sPTB) remains a significant global health challenge and a leading cause of neonatal mortality and morbidity. Despite advanc...

Multivariate Screening and Automated Clustering of Macrophage Immunoreactome to Nanoparticles and Photothermal Therapy.

Immunotherapy aims to control the immune system against diseases such as cancer or infections. Nanotechnology is part of the armamentarium to reprogra...

Magnetic-Assisted Manipulation of Rare Blood Cells for Diagnosis: A Systematic Review.

The precise isolation and analysis of rare cells from blood are crucial for biomedical research and clinical diagnostics. This review examines recent ...

Safety of nonselective nonsteroidal anti-inflammatory drugs in cardiac surgery: a historical cohort study.

PURPOSE: Pain management after cardiac surgery is imperative, as inadequate analgesia can increase the risk of myocardial ischemia, thromboembolism, a...

Comprehensive analysis and experimental validation of BST1 as a novel diagnostic biomarker for pediatric sepsis using multiple machine learning algorithms.

Bone marrow stromal cell antigen-1 (BST1) expression is elevated in a variety of human diseases, but its relationship with pediatric sepsis is unclear...

Towards a dynamic model to estimate evolving risk of major bleeding after percutaneous coronary intervention.

While static risk models may identify key driving risk factors, the dynamic nature of risk requires up-to-date risk information to guide treatment dec...

Artificial Intelligence in Hemophilia Management: Revolutionizing Patient Care and Future Directions.

Recent advancements in artificial intelligence (AI) hold significant promise for transforming hemophilia care. This review explores AI's impact on cri...

The early prediction of neonatal necrotizing enterocolitis in high-risk newborns based on two medical center clinical databases.

: Early identification and timely preventive interventions play an essential role for improving the prognosis of newborns with necrotizing enterocolit...

Physiological Response of Tissue-Engineered Vascular Grafts to Vasoactive Agents in an Ovine Model.

Tissue-engineered vascular grafts (TEVGs) are emerging as promising alternatives to synthetic grafts, particularly in pediatric cardiovascular surgery...

Machine Learning-Based Biomarker Discovery from Serum Trace Elements and Biochemical Parameters in Patients with Nasal Polyps.

Nasal polyps (NP) are benign mucosal outgrowths associated with chronic inflammation that can significantly reduce quality of life. This study aimed t...

Development and Validation of a Machine Learning-based Explainable Predictive Model for Long-term net Adverse Clinical Events in Patients With High Bleeding Risk Undergoing Percutaneous Coronary Intervention: Results From a Prospective Cohort Study.

BACKGROUND: Patients classified as having a high bleeding risk (HBR) and undergoing percutaneous coronary intervention (PCI) face a significantly grea...

Classification of primary glomerulonephritis using machine learning models: a focus on IgA nephropathy prediction.

OBJECTIVE: IgA nephropathy (IgAN) is the most common form of glomerulonephritis worldwide, characterized by immune complex deposition in the glomerula...

Identification of Migraine Subtypes Using Functional Near-Infrared Spectroscopy Data: A Domain-Based Feature Extraction.

Migraine diagnosis relies on subjective patient reports and International Headache Society guidelines, leading to misdiagnoses. In clinical practice, ...

A model developed by machine learning and principal component analysis for predicting bronchiolitis obliterans syndrome after allogeneic HSCT in a Chinese population with hematologic malignancies.

Bronchiolitis obliterans syndrome (BOS) is a severe pulmonary complication following allogeneic hematopoietic stem cell transplantation (allo-HSCT), w...

Prediction of biological evolution following blood product transfusion during liver transplantation: the contribution of machine learning to decision-making.

OBJECTIVES: Liver transplantation is a complex procedure frequently requiring transfusion of blood products to manage coagulopathy and haemorrhage. Th...

A machine learning model for mortality prediction in patients with severe fever with thrombocytopenia syndrome: a prospective, multicenter cohort study.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease that imposes a considerable medical burden. In this study, we enr...