Hematology

Machine learning-driven identification of shared and disease-specific mitochondria-related genes in COPD, NSCLC, and NSCLC with COPD.

Chronic obstructive pulmonary disease (COPD) and non-small-cell lung cancer (NSCLC) often coexist; here, the shared mitochondrial drivers were investigated. Serum from 30 subjects (seven controls, nine COPD, eight NSCLC, and six NSCLC with COPD) underwent RNA-seq, integrated with 1,136 MitoCarta 3.0-derived mitochondrial-related genes (MRGs). DESeq2 identified 25, 124, and 58 mitochondria-related ...

Machine learning models for early mortality prediction in severe fever with thrombocytopenia syndrome.

Severe fever with thrombocytopenia syndrome (SFTS) is a high-fatality viral disease where early mortality risk prediction is vital for clinical management. This retrospective multicenter cohort study enrolled 1,690 hospitalized SFTS patients from five Chinese hospitals (2014-2023) to develop, validate, and deploy an interpretable machine learning (ML) model for early mortality risk assessment. Usi...

Evaluating the methodological suitability of partial dependence plots and Shapley additive explanations for population-level interpretation of machine learning models in total joint arthroplasty.

BACKGROUND: Total joint arthroplasty (TJA) complications necessitate the development of accurate risk prediction models; however, interpretability in ...

Hemoglobin as a Molecular Glue: Toward Potent Inhibition of HbS Polymerization in Sickle Cell Disease.

Sickle cell disease (SCD), a monogenic disorder arising from a single point mutation in the β-globin gene, continues to pose a significant global heal...

Identification of Pyrrolo[2,3-d]pyrimidine-Based Dual MERTK and FLT3 Inhibitor: Hit-to-Lead, Machine Learning, Modeling, Synthesis, and Biological Evaluation.

Overexpression of MERTK and FLT3 plays a crucial role in activating signal transduction pathways in various human hematological malignancies. These si...

First-Trimester Machine Learning to Predict Preeclampsia in Normotensive Pregnancies by American Heart Association Guidelines.

This study aimed to determine whether unsupervised machine learning can identify phenotypically distinct subgroups at increased risk for preeclampsia ...

Detection of Antithrombotic-Related Bleeding in Older Inpatients: Multicenter Retrospective Study Using Structured and Unstructured Electronic Health Record Data.

BACKGROUND: Bleeding complications are a major contributor to adverse drug events among older inpatients, particularly in those treated with antithrom...

Tomek links-based SMOTE method for class imbalance in blood cell classification with dual path sliding window attention model.

Medical image processing has transformed the Complete Blood Count (CBC) analysis to enhance diagnostic accuracy and to detect diseases such as neurode...

From slides to AI-ready maps: Standardized multi-layer tissue maps as metadata for artificial intelligence in digital pathology.

A Whole Slide Image (WSI) is a high-resolution digital image created by scanning an entire glass slide containing a biological specimen, such as tissu...

A predictive mathematical framework for hemoglobin-material interactions: development of a hemoglobin sensitivity index (HSI) for next-generation biomedical applications.

Current biocompatibility assessment paradigms inadequately predict hemoglobin-material interactions, limiting the rational design of blood-contacting ...

Unbiased Characterization of Atrial Fibrillation Phenotypic Architecture Provides Insight Into Genetic Liability and Clinically Relevant Outcomes.

BACKGROUND: Atrial fibrillation (AF) is a common and clinically heterogeneous arrhythmia. Machine learning algorithms can define data-driven disease s...

In-hospital outcomes of intravascular lithotripsy compared to rotational atherectomy and cutting/scoring balloon angioplasty.

BACKGROUND: Intravascular lithotripsy (IVL) emerged for the treatment of coronary artery calcification with encouraging safety and effectiveness rates...

Lymphocyte-based inflammatory biomarkers during the postpartum period and postpartum depression symptoms in U.S. women.

BACKGROUND: Postpartum depression (PPD) has multiple cascading negative effects on maternal and infant health. Inflammation is a potential factor for ...

An integrative clinical and bioinformatic analysis identifies MicroRNAs as biomarkers of ischemic stroke severity.

Identifying reliable circulating biomarkers is crucial for improving the diagnosis and risk stratification of patients with ischemic stroke. In this s...

Advances in the pharmacology and mechanism of anti-skin aging in Tonifying Traditional Chinese Medicines.

ETHNOPHARMACOLOGICAL RELEVANCE: According to the Traditional Chinese Medicine (TCM) tenet that "internal imbalances manifest externally," skin aging r...

Machine learning-based prediction of three-year mortality in elderly inpatients with coronary artery disease combined with heart failure.

OBJECTIVE: Accurate prediction of survival outcome is essential for early intervention and treatment optimization. This study aimed to develop a model...

An Artificial Intelligence-Driven Platform for Practice Question Generation.

PROBLEM: High-stakes licensing exams such as the USMLE play a critical role in medical education, influencing both trainee progression and patient out...

Sickle cell disease detection in low-resource conditions using transfer-learning and contrastive-learning coupled with XAI.

Sickle cell disease (SCD) is a severe hereditary blood disorder that affects millions worldwide, necessitating early and accurate detection to improve...

Influencing Factors for Postembolization Fever in Patients Undergoing Transarterial Chemoembolization Based on Machine Learning: A Retrospective Study.

Although there is no framework for prediction models for postembolization fever, potential influencing factors include demographic, clinical, laborato...

Why Metrological Traceability Matters in Medical Laboratory Diagnostics.

Application of the results provided by medical laboratories plays an essential role in medical decision-making. This is not limited to diagnosis and m...