Hematology

Contrast-Enhanced Ultrasound for Hepatocellular Carcinoma Diagnosis- Expert Panel Narrative Review.

Despite growing clinical use of contrast-enhanced ultrasound (CEUS), inconsistency remains in the modality's role in clinical pathways for hepatocellular carcinoma (HCC) diagnosis and management. This AJR Expert Panel Narrative Review provides practical insights on the use of CEUS for the diagnosis of HCC across populations, including individuals at high risk for HCC, individuals with metabolic dy...

Machine learning algorithms with body fluid parameters: an interpretable framework for malignant cell screening in cerebrospinal fluid.

OBJECTIVES: This study aimed to develop and validate a machine learning (ML) model utilizing cerebrospinal fluid (CSF) body fluid parameters from hematology analyzers to screen for malignant cells.

Hemoglobin - to - red cell distribution width ratio in depression symptoms: Threshold effects and metabolic - inflammatory mediation revealed by multimodal machine learning and symptom network analysis in 196,260 adults.

OBJECTIVE: To investigate the association between hemoglobin to red blood cell distribution width ratio (HRR) and depression symptoms.

Tilorone attenuates high-fat diet-induced hepatic steatosis by enhancing BMP9-Smad1/5/8 signaling.

The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) is rapidly increasing and is caused by excessive fat deposition in ...

Emerging blood biomarkers in Alzheimer's disease: a proteomic perspective.

Early detection of Alzheimer's disease (AD) remains a formidable clinical challenge, but emerging blood-based assays show promise for identifying at-r...

A new dataset for measuring the performance of blood vessel segmentation methods under distribution shifts.

Creating a dataset for training supervised machine learning algorithms can be a demanding task. This is especially true for blood vessel segmentation ...

Drug repurposing to identify potential FDA-approved drugs targeting three main angiogenesis receptors through a deep learning framework.

Tumor cell survival depends on the presence of oxygen and nutrients provided by existing blood vessels, particularly when cancer is in its early stage...

Advances in brain-targeted delivery strategies and natural product-mediated enhancement of blood-brain barrier permeability.

The blood-brain barrier (BBB) represents a formidable challenge in the treatment of neurological disorders, as it restricts the passage of most therap...

Prediction of mild cognitive impairment using blood multi-omics data.

Mild cognitive impairment (MCI) represents an initial phase of memory or other cognitive function decline and is viewed as an intermediary stage betwe...

A Wearable In-Pad Diagnostic for the Detection of Disease Biomarkers in Menstruation Blood.

The pain-free monitoring of blood-based biomarkers is essential for early detection of diseases like cancers, infections, and metabolic disorders such...

Deep ensemble framework with Bayesian optimization for multi-lesion recognition in capsule endoscopy images.

In order to address the challenges posed by the large number of images acquired during wireless capsule endoscopy examinations and fatigue-induced lea...

Association between fibrinogen levels and prognosis in critically bleeding patients: exploration of the optimal therapeutic threshold.

BACKGROUND: Severe bleeding is a leading cause of ICU admission and mortality. Fibrinogen plays a crucial role in prognosis, yet optimal thresholds an...

Non-invasive arterial input function estimation using an MRA atlas and machine learning.

BACKGROUND: Quantifying biological parameters of interest through dynamic positron emission tomography (PET) requires an arterial input function (AIF)...

Comparative evaluation of six large language models in transfusion medicine: Addressing language and domain-specific challenges.

BACKGROUND AND OBJECTIVES: Large language models (LLMs) such as GPT-4 are increasingly utilized in clinical and educational settings; however, their v...

Biallelic loss-of-function variants in ZNF142 are associated with a robust DNA methylation signature affecting a limited number of genomic loci.

Biallelic inactivating variants in ZNF142 underlie a clinically variable neurodevelopmental disorder. ZNF142 is a zinc-finger transcription factor wit...

Deep Learning-Based Aortic Diameter Measurement in Traumatic Hemorrhage Using Shallow Attention Network: A Path Forward.

The accurate assessment of aortic diameter (AoD) is essential in managing patients with traumatic hemorrhage, particularly during interventions such ...

Using Machine Learning to Predict Linezolid-Associated Thrombocytopenia.

OBJECTIVE: Using artificial intelligence and machine learning to predict linezolid-induced thrombocytopenia helps identify related risk factors in pat...

Construction of a predictive model for relapse of primary autoimmune hemolytic anemia: a retrospective cohort study.

OBJECTIVES: To develop a machine learning-based model to predict the relapse risk of Primary Autoimmune Haemolytic Anaemia (AIHA) after the last remis...

Evaluating Large Language Models on American Board of Anesthesiology-style Anesthesiology Questions: Accuracy, Domain Consistency, and Clinical Implications.

Recent advances in large language models (LLMs) have led to growing interest in their potential applications in medical education and clinical practic...

Predicting Postoperative Blood Transfusion in Elderly Patients Undergoing Total Hip and Knee Arthroplasty Using Machine Learning Models.

PURPOSE: With the aging population, the demand for total hip arthroplasty (THA) and total knee arthroplasty (TKA) has risen significantly. Elderly pat...