Hematology

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

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Prediction model for cardiovascular disease in patients with diabetes using machine learning derived and validated in two independent Korean cohorts.

This study aimed to develop and validate a machine learning (ML) model tailored to the Korean popula...

Explainable AI based automated segmentation and multi-stage classification of gastroesophageal reflux using machine learning techniques.

Presently, close to two million patients globally succumb to gastrointestinal reflux diseases (GERD)...

Optical imaging for diabetic retinopathy diagnosis and detection using ensemble models.

Diabetes, characterized by heightened blood sugar levels, can lead to a condition called Diabetic Re...

Supervised Machine Learning-Based Models for Predicting Raised Blood Sugar.

Raised blood sugar (hyperglycemia) is considered a strong indicator of prediabetes or diabetes melli...

Optimization of mid-infrared noninvasive blood-glucose prediction model by support vector regression coupled with different spectral features.

Mid-infrared spectral analysis of glucose in subcutaneous interstitial fluid has been widely employe...

Making sense of artificial intelligence and large language models-including ChatGPT-in pediatric hematology/oncology.

ChatGPT and other artificial intelligence (AI) systems have captivated the attention of healthcare p...

A machine learning model predicts stroke associated with blood cadmium level.

Stroke is the leading cause of death and disability worldwide. Cadmium is a prevalent environmental ...

Sex dimorphism of IL-17-secreting peripheral blood mononuclear cells in ankylosing spondylitis based on bioinformatics analysis and machine learning.

BACKGROUND: Ankylosing spondylitis (AS) with radiographic damage is more prevalent in men than in wo...

Determination of prognostic markers for COVID-19 disease severity using routine blood tests and machine learning.

The need for the identification of risk factors associated to COVID-19 disease severity remains urge...

Glycocalyx shedding patterns identifies antipsychotic-naïve patients with first-episode psychosis.

Psychotic disorders have been linked to immune-system abnormalities, increased inflammatory markers,...

Development and validation of machine learning models to predict perioperative transfusion risk for hip fractures in the elderly.

BACKGROUND: Patients with hip fractures frequently need to receive perioperative transfusions of con...

Validation of a Machine Learning Algorithm, EVendo, for Predicting Esophageal Varices in Hepatocellular Carcinoma.

BACKGROUND: Treatment with atezolizumab and bevacizumab has become standard of care for advanced unr...

Testing Machine Learning Models to Predict Postoperative Ileus after Colorectal Surgery.

Postoperative ileus (POI) is a common complication after colorectal surgery, leading to increased h...

A new methodology for determining the central pressure waveform from peripheral measurement using Fourier-based machine learning.

Radial applanation tonometry is a well-established technique for hemodynamic monitoring and is becom...

Leveraging deep learning for detecting red blood cell morphological changes in blood films from children with severe malaria anaemia.

In sub-Saharan Africa, acute-onset severe malaria anaemia (SMA) is a critical challenge, particularl...

Improving platelet-RNA-based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification.

Liquid biopsy demonstrates excellent potential in patient management by providing a minimally invasi...

Smart solutions in hypertension diagnosis and management: a deep dive into artificial intelligence and modern wearables for blood pressure monitoring.

Hypertension, a widespread cardiovascular issue, presents a major global health challenge. Tradition...

Performance Evaluation of a Novel Artificial Intelligence-Assisted Digital Microscopy System for the Routine Analysis of Bone Marrow Aspirates.

Bone marrow aspiration (BMA) smear analysis is essential for diagnosis, treatment, and monitoring of...

Prediction of post-delivery hemoglobin levels with machine learning algorithms.

Predicting postpartum hemorrhage (PPH) before delivery is crucial for enhancing patient outcomes, en...

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