Hematology

Improving mortality prediction in critically ill cancer patients with a multidimensional machine learning model.

BACKGROUND: Prognostic assessment in critically ill cancer patients is challenging due to the subopt...

Edge-prior and reliability-guided collaborative learning for white blood cell classification.

Accurate white blood cell (WBC) classification is important for hematological screening and computer...

When artificial intelligence meets musculoskeletal ultrasound in hemophilia.

AI-assisted Radiomic Model for Cervical Cancer Recurrence Prediction: A Multicenter Retrospective Study with Experimental Validation.

Purpose To evaluate the value of a nomogram model incorporating clinical parameters, hematologic inf...

An Explainable Machine Learning Model for Early Prediction of Incident Myocardial Injury in Patients With Severe Fever With Thrombocytopenia Syndrome.

This study aimed to develop an explainable machine learning-based model to enable early prediction o...

Advances and prospects in cell therapy for cancer: explorations from T cells to stem cells.

The increasing global burden of cancer necessitates innovative therapeutic strategies. Cell therapy ...

Detecting Adverse Events Following Acute Care Encounters among Veterans Prescribed Non-Steroidal Anti-Inflammatory Drugs.

OBJECTIVES: To model the occurrence of adverse events (AEs) among Veterans prescribed nonsteroidal a...

Non-invasive estimation of hemoglobin using machine learning algorithms from i-PPG and PPG signals.

Significant research works have been carried out in the area of non-invasive hemoglobin estimation i...

Comparative machine learning approaches to prognosticate clinical outcomes in oral and maxillofacial space infections: a retrospective analysis.

BACKGROUND: The objective of this study was to evaluate the performance of multiple machine learning...

Trajectory analysis of sleep disorders and anxiety-depression in female breast cancer patients undergoing chemotherapy: based on group-based Multi-Trajectory Model and machine learning.

BACKGROUND: Sleep disorders and anxiety-depression symptoms can significantly impair the quality of ...

Approaches to transcatheter aortic valve replacement failure: is more focus on prevention required?

INTRODUCTION: Transcatheter aortic valve replacement (TAVR) has transformed the management of severe...

The HLH-Risk-Calculator is a machine learning-based tool to predict course & mortality of secondary hemophagocytic lymphohistiocytosis.

PURPOSE: Secondary hemophagocytic lymphohistiocytosis (sHLH) is a life-threatening hyperinflammatory...

Postoperative cerebral infarction after major thoracic and abdominopelvic surgery: a retrospective single-centre cohort study of incidence, risk factors, and outcomes.

BACKGROUND: Postoperative cerebral infarction (POCI) is an uncommon but potentially fatal complicati...

A Novel Machine Learning Approach for Predicting Prognosis of SFTS Patients in the Early Stages of Disease.

OBJECTIVE: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne disease char...

SegMWB: A lightweight deep learning framework for microscopic image classification.

White Blood Cells (WBCs) play a significant role in assessing an individual's health. An automated W...

Discovery of biomarkers for primary Sj ögren's syndrome based on multi-omics data, construction of diagnostic models, and clinical correlation analysis.

OBJECTIVE: Primary Sjogren's syndrome(pSS) exhibits significant clinical heterogeneity, which poses ...

Secondary prevention of recurrent ischemic stroke: from guidelines to precision medicine.

Recurrent ischemic stroke remains a major global health challenge, accounting for substantial disabi...

Integrating Machine Learning and Pharmacology Reveals NF-κB-Mediated Inflammatory Regulation by Shuanghuanglian Injection in Acute Lung Injury.

ETHNOPHARMACOLOGICAL RELEVANCE: Shuanghuanglian Injection (SHLI) is a traditional Chinese medicine f...

Assessment of the accuracy and readability of artificial generative intelligence for patient questions on heavy menstrual bleeding.

OBJECTIVES: To evaluate the quality, patient-centeredness, clinician endorsement, and readability of...

Diagnostic Accuracy of Artificial Intelligence-based Automated Detection of Diabetic Retinopathy in Routine Care Using Nonmydriatic Fundus Images: The Silesia Diabetes-Heart Project.

PURPOSE: To evaluate the diagnostic performance of a regulatory-approved (CE-marked) artificial inte...

An interpretable machine learning model integrating peripheral blood lncRNAs and clinical variables for phase classification in chronic myeloid leukemia.

BACKGROUND: Accurate disease phase assessment remains clinically important in chronic myeloid leukem...