Hematology

Blood cancer prediction model based on deep learning technique.

Blood cancer is among the critical health concerns among people around the world and normally emanat...

Evaluating the accuracy of ChatGPT in classifying normal and abnormal blood cell morphology.

Utilizing artificial intelligence and cellular population data for timely identification of bacteremia in hospitalized patients.

BACKGROUND: Bacteremia is a critical condition with high mortality that requires prompt detection to...

Combining machine learning and single-cell sequencing to identify key immune genes in sepsis.

This research aimed to identify novel indicators for sepsis by analyzing RNA sequencing data from pe...

Non-Invasive Cancer Detection Using Blood Test and Predictive Modeling Approach.

PURPOSE: The incidence of cancer, which is a serious public health concern, is increasing. A predict...

Applying artificial intelligence to uncover the genetic landscape of coagulation factors.

Artificial intelligence (AI) is rapidly advancing our ability to identify and interpret genetic vari...

Diagnostic Accuracy of Ambient Mass Spectrometry with Blood Plasma in a Murine Glioma Model Using Machine Learning.

OBJECTIVE: Malignant glioma progresses rapidly and shows poor prognosis, but clinically applicable b...

Genomic determinants of biological age estimated by deep learning applied to retinal images.

With the development of deep learning (DL) techniques, there has been a successful application of th...

The role of endothelial cell-related gene COL1A1 in prostate cancer diagnosis and immunotherapy: insights from machine learning and single-cell analysis.

BACKGROUND: Endothelial cells are integral components of the tumor microenvironment and play a multi...

Blood metal levels predict digestive tract cancer risk using machine learning in a U.S. cohort.

BACKGROUND: Environmental metal exposure has been implicated in the development of digestive tract c...

Uncovering blood-brain barrier permeability: a comparative study of machine learning models using molecular fingerprints, and SHAP explainability.

This study illustrates the use of chemical fingerprints with machine learning for blood-brain barrie...

Diagnostic and prognostic perspectives of Fabry disease via fiber evanescent wave spectroscopy advanced by machine learning.

Fabry disease (FD) is a rare disorder resulting from a genetic mutation characterized by the accumul...

rU-Net, Multi-Scale Feature Fusion and Transfer Learning: Unlocking the Potential of Cuffless Blood Pressure Monitoring With PPG and ECG.

This study introduces an innovative deep-learning model for cuffless blood pressure estimation using...

Predicting Blood Pressures for Pregnant Women by PPG and Personalized Deep Learning.

Blood pressure (BP) is predicted by this effort based on photoplethysmography (PPG) data to provide ...

Correlation between the white blood cell/platelet ratio and 28-day all-cause mortality in cardiac arrest patients: a retrospective cohort study based on machine learning.

OBJECTIVE: This study aims to evaluate the association between the white blood cell-to-platelet rati...

Retrospective cohort study based on the MIMIC-IV database: analysis of factors influencing all-cause mortality at 30 days, 90 days, 1 year, and 3 years in patients with different types of stroke.

OBJECTIVE: This study aims to evaluate key factors influencing the short-term and long-term prognosi...

Machine learning models based on FEM simulation of hoop mode vibrations to enable ultrasonic cuffless measurement of blood pressure.

Blood pressure (BP) is one of the vital physiological parameters, and its measurement is done routin...

Classification of α-thalassemia data using machine learning models.

BACKGROUND: Around 7% of the global population has congenital hemoglobin disorders, with over 300,00...

Predictive modeling of consecutive intravenous immunoglobulin treatment resistance in Kawasaki disease: A nationwide study.

Kawasaki disease (KD) is a leading cause of acquired heart disease in children, often resulting in c...

An effective vessel segmentation method using SLOA-HGC.

Accurate segmentation of retinal blood vessels from retinal images is crucial for detecting and diag...

Xixin Decoction's novel mechanism for alleviating Alzheimer's disease cognitive dysfunction by modulating amyloid-β transport across the blood-brain barrier to reduce neuroinflammation.

PURPOSE: Xixin Decoction (XXD) is a classical formula that has been used to effectively treat dement...