Hematology

Prediction model for ctDNA detectability in liquid comprehensive genomic profiling of advanced pancreatic cancer based on Japanese real-world data.

BACKGROUND: Circulating tumor DNA (ctDNA) is sometimes undetectable in liquid comprehensive genomic profiling (CGP) of advanced-stage pancreatic cancer, resulting in false-negative findings that may mislead treatment decisions and waste health care resources. Predicting ctDNA detectability before testing may help optimize the timing of liquid CGP and guide decisions to consider alternative approac...

Deep Learning and Machine Learning for Differentiation Between Contrast Extravasation and Hemorrhagic Transformation in Post-Thrombectomy Stroke CT.

BACKGROUND: Mechanical thrombectomy (MT) improves outcomes in acute ischemic stroke (AIS) but often results in hyperdensities on non-contrast CT (NCCT), which may represent either hemorrhagic transformation (HT) or contrast extravasation (CE). Distinguishing between them is critical, as HT may contraindicate early anticoagulation. We developed and validated machine learning (ML) models to differen...

The use of advanced machine learning to predict outcomes after atezolizumab plus bevacizumab for advanced hepatocellular carcinoma: a retrospective cohort study.

BACKGROUND: Combination immune checkpoint inhibitors are recommended as first-line therapy for advanced hepatocellular carcinoma. However, only a thir...

Association of Circulating T Cell and Tumor Microenvironment Profiles with Immune Checkpoint Blockade Outcome in Sarcoma.

PURPOSE: Immune checkpoint blockade (ICB) benefits only a subset of sarcoma patients. Biomarkers of response and resistance are needed to help guide p...

Volume electron microscopy reveals heterogeneity of the hemostatic response in veins and arteries.

Intravital imaging studies have provided insights into the spatial and temporal variations of platelet activation and thrombin generation that occur d...

Development and evaluation of a prediction model for adult ICU hemorrhage using only continuous cardiorespiratory data.

Develop and evaluate whether a model trained to detect the physiological signature of hemorrhage in ICU patients generalizes to other cohorts. App...

[Application of a novel robot-assisted navigation system in CT-guided percutaneous lung biopsy].

Objective: To compare the clinical efficacy and safety of robot-assisted navigation systems with those of the conventional puncture localization metho...

Machine learning for hemodynamic instability prediction and hemorrhage management in trauma and perioperative care.

PURPOSE OF REVIEW: Hemodynamic instability and uncontrolled hemorrhage remain leading causes of preventable morbidity and mortality in trauma and peri...

Real-time, artificial intelligence-guided intraoperative resuscitation and fluid management in trauma anesthesia.

PURPOSE OF REVIEW: To synthesize recent advances in intraoperative resuscitation for trauma surgery, including fluid composition, transfusion threshol...

[Cardiology : what's new in 2025].

In 2025, significant progress has been made in the management of heart failure and cardiovascular diseases, driven by the emergence of new treatments ...

Comparison and validation of multiple machine learning algorithms for predicting MDRO infection in catheter-related bloodstream patients: a multicenter cohort study.

UNLABELLED: Early identification of patients at high risk for multidrug-resistant organism (MDRO) infection in catheter-related bloodstream infection ...

Preoperative lymphocyte signature predicts pancreatic fistula after pancreatoduodenectomy.

BACKGROUND: Postoperative pancreatic fistula (POPF) is the major driver of postoperative morbidity after pancreatoduodenectomy (PD) and a healthcare i...

Periodontitis Prediction Model Using Linked Electronic Health and Dental Records.

INTRODUCTION: Periodontal disease (PD) is closely linked to systemic health, with established associations with chronic conditions (eg, diabetes, card...

Detection of esophageal varices and prediction of hepatic decompensation in unresectable hepatocellular carcinoma using AI.

BACKGROUND & AIMS: In hepatocellular carcinoma (HCC) with cirrhosis, portal hypertension worsens outcomes. Esophagogastroduodenoscopy (EGD), the curre...

Mechanistic investigation and data-driven correction of lipemic interference in hematological parameters on the Mindray BC-6800 hematology analyzer.

OBJECTIVES: This study aimed to systematically investigate the interference of lipemia on the Mindray BC-6800 hematology analyzer, elucidate the under...

Comprehensive dataset on macro-porous PVDF flat sheet membranes for membrane distillation: Materials characteristics, morphology and performance data.

This data article presents a structured dataset from the transfer of a proven PVDF hollow-fiber formulation to macro-porous PVDF flat sheet membranes ...

Data-driven subgroups for 3-year risk stratification of incident diabetes and complications in diabetes-free Chinese adults.

BACKGROUND: Substantial metabolic heterogeneity exists prior to the development of diabetes, creating opportunities for earlier and more precise inter...

Practical machine learning model for early and accurate prediction of disseminated intravascular coagulation before its progression to an overt stage.

BACKGROUND AND AIMS: In patients with sepsis, anticoagulant therapy is expected to have maximal efficacy when administered before the development of s...

Alzheimer's disease prediction using deep learning and XAI based interpretable feature selection from blood gene expression data.

Alzheimer's disease (AD), a type of neurodegenerative disorder, has seen an increase in cases over the past decade, necessitating the construction of ...

Artificial intelligence in trauma care: applications, ethical challenges, and pathways toward responsible integration.

PURPOSE OF REVIEW: Artificial intelligence is increasingly applied across the trauma care continuum, from prehospital triage to in-hospital decision-m...