Hematology

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

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The Application of Machine Learning in Predicting the Permeability of Drugs Across the Blood Brain Barrier.

The inefficiency of some medications to cross the blood-brain barrier (BBB) is often attributed to t...

Antigen-independent single-cell circulating tumor cell detection using deep-learning-assisted biolasers.

Circulating tumor cells (CTCs) in the bloodstream are important biomarkers for clinical prognosis of...

Shortcomings in the Evaluation of Blood Glucose Forecasting.

OBJECTIVE: Recent years have seen an increase in machine learning (ML)-based blood glucose (BG) fore...

A Near-Infrared Imaging System for Robotic Venous Blood Collection.

Venous blood collection is a widely used medical diagnostic technique, and with rapid advancements i...

A machine learning prediction model for Cardiac Amyloidosis using routine blood tests in patients with left ventricular hypertrophy.

Current approaches for cardiac amyloidosis (CA) identification are time-consuming, labor-intensive, ...

AI-Based Noninvasive Blood Glucose Monitoring: Scoping Review.

BACKGROUND: Current blood glucose monitoring (BGM) methods are often invasive and require repetitive...

Artificial intelligence in cytopathological applications for cancer: a review of accuracy and analytic validity.

BACKGROUND: Cytopathological examination serves as a tool for diagnosing solid tumors and hematologi...

Computer tomography-based radiomics combined with machine learning for predicting the time since onset of epidural hematoma.

Estimation of the age of epidural hematoma (EDH) is a challenge in clinical forensic medicine, and t...

Diagnosis and typing of leukemia using a single peripheral blood cell through deep learning.

Leukemia is highly heterogeneous, meaning that different types of leukemia require different treatme...

Transparent Machine Learning Model to Understand Drug Permeability through the Blood-Brain Barrier.

The blood-brain barrier (BBB) selectively regulates the passage of chemical compounds into and out o...

Magnetic soft microrobots for erectile dysfunction therapy.

Erectile dysfunction (ED) is a major threat to male fertility and quality of life, and mesenchymal s...

Deep learning-based automatic bleeding recognition during liver resection in laparoscopic hepatectomy.

BACKGROUND: Intraoperative hemorrhage during laparoscopic hepatectomy (LH) is a risk factor for nega...

MIMIC-BP: A curated dataset for blood pressure estimation.

Blood pressure (BP) is one of the most prominent indicators of potential cardiovascular disorders. T...

Artificial intelligence modeling of biomarker-based physiological age: Impact on phase 1 drug-metabolizing enzyme phenotypes.

Age and aging are important predictors of health status, disease progression, drug kinetics, and eff...

Ultrasensitive Detection of Blood-Based Alzheimer's Disease Biomarkers: A Comprehensive SERS-Immunoassay Platform Enhanced by Machine Learning.

Accurate and early disease detection is crucial for improving patient care, but traditional diagnost...

Identification of TXN and F5 as novel diagnostic gene biomarkers of the severe asthma based on bioinformatics and machine learning analysis.

Asthma poses a major threat to human health. The aim of this study was to identify genetic markers o...

SNPs and blood inflammatory marker featured machine learning for predicting the efficacy of fluorouracil-based chemotherapy in colorectal cancer.

Fluorouracil-based chemotherapy responses in colorectal cancer (CRC) patients vary widely, highlight...

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