Hematology

Latest AI and machine learning research in hematology for healthcare professionals.

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Development and validation of a machine learning-based model for predicting intraoperative blood loss during burn surgery.

BACKGROUND: Intraoperative blood loss is a critical issue in the care of patients with burns. The ti...

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 cerebro...

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

Despite growing clinical use of contrast-enhanced ultrasound (CEUS), inconsistency remains in the mo...

Blood pressure monitoring is key in aortic dissection.

Blood pressure (BP) control is essential for both the prevention and long-term management of aortic ...

Global research trends in AI-assisted blood glucose management: a bibliometric study.

BACKGROUND: AI-assisted blood glucose management has become a promising method to enhance diabetes c...

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

Early detection of Alzheimer's disease (AD) remains a formidable clinical challenge, but emerging bl...

A bidirectional reasoning approach for blood glucose control via invertible neural networks.

BACKGROUND AND OBJECTIVE: Despite the profound advancements that deep learning models have achieved ...

Immunogenic cell death biomarkers for sepsis diagnosis and mechanism via integrated bioinformatics.

Immunogenic cell death (ICD) has been implicated in sepsis, a condition with high mortality, through...

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 increa...

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...

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 dis...

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

Mild cognitive impairment (MCI) represents an initial phase of memory or other cognitive function de...

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 caps...

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...

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 h...

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...

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 c...

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

BACKGROUND: Quantifying biological parameters of interest through dynamic positron emission tomograp...

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