Hematology

Single-center outcomes of artificial intelligence in management of pulmonary embolism and pulmonary embolism response team activation.

Multidisciplinary pulmonary embolism response teams (PERTs) have shown that timely triage expedites treatment. The use of artificial intelligence (AI) may help improve pulmonary embolism (PE) management with early CT pulmonary angiogram (CTPA) screening and accelerate PERT coordination. This study aimed to test the clinical validity of an FDA-approved PE AI algorithm. CTPA scan data of 200 patient...

Machine Learning Predicts Peripherally Inserted Central Catheters-Related Deep Vein Thrombosis Using Patient Features and Catheterization Technology Features.

This study aims to use patient feature and catheterization technology feature variables to train the corresponding machine learning (ML) models to predict peripherally inserted central catheters-deep vein thrombosis (PICCs-DVT) and analyze the importance of the two types of features to PICCs-DVT from the aspect of "input-output" correlation. To comprehensively and systematically summarize the vari...

Machine learning identifies key cells and therapeutic targets during ferroptosis after spinal cord injury.

JOURNAL/nrgr/04.03/01300535-202606000-00064/figure1/v/2026-02-11T151048Z/r/image-tiff Ferroptosis, a type of cell death that mainly involves iron meta...

An attention-based deep learning for acute lymphoblastic leukemia classification.

The bone marrow overproduces immature cells in the malignancy known as Acute Lymphoblastic Leukemia (ALL). In the United States, about 6500 occurrence...

Machine learning-based prediction model of lower extremity deep vein thrombosis after stroke.

This study aimed to apply machine learning (ML) techniques to develop and validate a risk prediction model for post-stroke lower extremity deep vein t...

Machine learning allows robust classification of visceral fat in women with obesity using common laboratory metrics.

The excessive accumulation and malfunctioning of visceral adipose tissue (VAT) is a major determinant of increased risk of obesity-related comorbiditi...

Evaluation of the Factors Influencing Blood Transfusion during Minimally Invasive Direct Coronary Artery Bypass Surgery.

INTRODUCTION: The objective of this study was to analyze the blood transfusion factors of minimally invasive direct coronary artery bypass (MIDCAB) su...

Prediction of leukemia peptides using convolutional neural network and protein compositions.

Leukemia is a type of blood cell cancer that is in the bone marrow's blood-forming cells. Two types of Leukemia are acute and chronic; acute enhances ...

Evaluation of artificial intelligence-assisted morphological analysis for platelet count estimation.

INTRODUCTION: This study aims to assess the performance of the platelet count estimation using artificial intelligence technology on the MC-80 digital...

Retrospective analysis of interpretable machine learning in predicting ICU thrombocytopenia in geriatric ICU patients.

We developed an interpretable machine learning algorithm that prospectively predicts the risk of thrombocytopenia in older critically ill patients dur...

Development, validation, and usability evaluation of machine learning algorithms for predicting personalized red blood cell demand among thoracic surgery patients.

INTRODUCTION: Preparing appropriate red blood cells (RBCs) before surgery is crucial for improving both the efficacy of perioperative workflow and pat...

Machine/deep learning-assisted hemoglobin level prediction using palpebral conjunctival images.

Palpebral conjunctival hue alteration is used in non-invasive screening for anaemia, whereas it is a qualitative measure. This study constructed machi...

Development of a machine learning approach for prediction of red blood cell transfusion in patients undergoing Cesarean section at a single institution.

Despite recent advances in surgical techniques and perinatal management in obstetrics for reducing intraoperative bleeding, blood transfusion may occu...

Multi-parameter MRI-Based Machine Learning Model to Evaluate the Efficacy of STA-MCA Bypass Surgery for Moyamoya Disease: A Pilot Study.

Superficial temporal artery-middle cerebral artery (STA-MCA) bypass surgery represents the primary treatment for Moyamoya disease (MMD), with its effi...

Transforming Hypertension Diagnosis and Management in The Era of Artificial Intelligence: A 2023 National Heart, Lung, and Blood Institute (NHLBI) Workshop Report.

Hypertension is among the most important risk factors for cardiovascular disease, chronic kidney disease, and dementia. The artificial intelligence (A...

Machine learning models predict triage levels, massive transfusion protocol activation, and mortality in trauma utilizing patients hemodynamics on admission.

BACKGROUND: The effective management of trauma patients necessitates efficient triaging, timely activation of Massive Blood Transfusion Protocols (MTP...

At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods.

By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mor...

Machine learning-based prediction of diabetic patients using blood routine data.

Diabetes stands as one of the most prevalent chronic diseases globally. The conventional methods for diagnosing diabetes are frequently overlooked unt...

Artificial neural network modeling for the prediction, estimation, and treatment of diverse wastewaters: A comprehensive review and future perspective.

The application of artificial neural networks (ANNs) in the treatment of wastewater has achieved increasing attention, as it enhances the efficiency a...

Future Perspectives of Artificial Intelligence in Bone Marrow Dosimetry and Individualized Radioligand Therapy.

Radioligand therapy is an emerging and effective treatment option for various types of malignancies, but may be intricately linked to hematological si...