Hematology

Integrating CAR-T therapy with PD-1/PD-L1 blockade: Mechanisms, synergy, and optimized strategies in NSCLC.

Non-small cell lung cancer (NSCLC) presents persistent challenges in immunotherapy, as the clinical benefit of programmed cell death protein 1 (PD-1) and programmed death-ligand 1 (PD-L1) inhibitors is frequently constrained by intrinsic and acquired resistance. Central contributors include impaired antigen presentation, T cell exclusion, and the accumulation of immunosuppressive populations that ...

Dynamic Ensemble Selection for Early Detection of Deep Vein Thrombosis in Fracture Patients.

Deep vein thrombosis (DVT) in fracture patients is often clinically silent, with a high incidence of thrombosis and associated mortality. Static machine learning methods struggle to address the challenge of early DVT diagnosis due to their inability to adapt to heterogeneous data across patients. In contrast, Dynamic Ensemble Selection (DES) improves clinical decision-making and therapeutic interv...

Assessment of AI-generated responses to common pregnancy questions: A blinded expert evaluation.

INTRODUCTION: We conducted a cross-sectional, blinded expert evaluation of AI-generated answers to 22 frequently asked pregnancy questions to characte...

Components of metabolic syndrome affect COVID-19 outcomes via platelet aggregation.

BACKGROUND: Emerging evidence suggests that platelet activation and aggregation are common factors in both metabolic syndrome (MetS) and severe COVID-...

The 2025 top 10 list of endoscopy topics in medical publishing: an annual review by the American Society for Gastrointestinal Endoscopy Editorial Board.

Using a systematic literature search of original articles published during 2025 in Gastrointestinal Endoscopy (GIE) and other high-impact medical and ...

Programmable Smart CAR-T design: A new paradigm in precision immunotherapy driven by logic gates, conditional activation, allogeneic strategies, and artificial intelligence.

Chimeric antigen receptor T-cell (CAR-T) therapy has achieved unprecedented success in hematological malignancies but faces formidable challenges in s...

Lightweight interpretable AI model using multiple blood parameters for emergency diagnosis of acute appendicitis.

BACKGROUND: Acute appendicitis poses diagnostic challenges due to symptom overlap with other abdominal conditions, often leading to misdiagnosis or mi...

Cascade machine learning reveals the regulatory mechanism of dissolved organic matter on nanoparticles aggregation behavior.

The aggregation of nanoparticles (NPs) in aquatic environments is influenced by multiple environmental conditions, with dissolved organic matter (DOM)...

Predicting Chronicity in Children and Adolescents With Newly Diagnosed Immune Thrombocytopenia at the Timepoint of Diagnosis Using Machine Learning-Based Approaches.

OBJECTIVES: To identify predictors of chronic ITP (cITP) and to develop a model based on several machine learning (ML) methods to estimate the individ...

A clinical dataset on type-2 diabetes including demographic, anthropometric, and biochemical parameters from Bangladesh.

Type-2 diabetes is a major public health concern in Bangladesh, and this dataset provides 1065 curated patient records with demographic, anthropometri...

A study on user satisfaction with medical devices for the elderly: The case of blood pressure monitors.

Against the backdrop of global population ageing, cognitive decline not only limits the quality of life for older adults but also presents a critical ...

FGA Serves as a Potential Diagnostic Marker and Therapeutic Target for Elderly Acute Kidney Injury.

To identify potential biomarkers and explore the underlying mechanisms of elderly acute kidney injury (e-AKI), we performed integrative plasma proteom...

Comparison of blood sample quality and test results between robotic and manual venipuncture: a pilot study.

OBJECTIVES: This study aimed to evaluate the feasibility of robotic venipuncture in clinical settings and compare its performance with manual venipunc...

Machine learning models for predicting postoperative complications following mandibular third molar surgery: Development, validation, and explainable AI insights.

The surgical removal of impacted mandibular third molars is a routine procedure in oral and maxillofacial surgery but is consistently associated with ...

Beyond Fine-Tuning: Leveraging Domain-Aware In-Context learning with large language models for clinical named entity recognition.

BACKGROUND: Clinical named entity recognition (NER) is essential for structuring clinical narratives. While large language model (LLM)-based in-contex...

Immunoprotective and neuroprotective properties of gut microbiome in psoriasis.

Psoriasis impacts nearly 100 million people globally and is associated with neuropsychiatric comorbidities such as depression and anxiety. With gut mi...

YiQiFuMai ameliorates hypoperfusion-induced cerebral infarction by targeting the shear stress-PLBD1-glycolysis-angiogenesis axis.

BACKGROUND: Hypoperfusion-induced cerebral infarction remains a significant therapeutic challenge due to limited treatment options. Yiqi Fumai (YQFM),...

Clinical applications of artificial intelligence-driven nitric oxide: a bibliometric and scientific mapping analysis.

JOURNAL/mgres/04.03/01612956-202609000-00002/figure1/v/2026-01-06T135433Z/r/image-tiff Nitric oxide, a pivotal endogenous signaling molecule, plays cr...

Machine learning reveals sex-biased platelet-associated molecular signatures in systemic lupus erythematosus.

OBJECTIVES: Autoimmune diseases (ADs) demonstrate a higher prevalence in women than men. Systemic Lupus Erythematosus (SLE) stands out among multiple ...

Association between the platelet to white blood cell ratio and short term mortality in critically ill patients with atherosclerotic cardiovascular disease: A retrospective study and machine learning with external validation.

BACKGROUND: The platelet to white blood cell ratio (PWR) has shown prognostic value in many diseases. Yet its predictive utility for patients with ath...