Leukemia

Deep learning cascade networks for segmentation of fluorine-18 sodium fluoride positron emission tomography scans of equine metacarpo- and metatarsophalangeal joints outperform atlas-based method.

OBJECTIVE: To create a labeled dataset and evaluate a convolutional neural network (CNN) for segmentation of fluorine-18 sodium fluoride PET scans of the equine metacarpo- and metatarsophalangeal joint (fetlock), targeting the third metacarpal bone, proximal phalanx, proximal sesamoid bone(s), and soft tissue. METHODS: PET and corresponding CT scans were retrospectively selected from June 2024 thr...

Machine learning-based prediction of significant intraoperative blood loss to guide risk-adapted blood management decisions in spinal surgery.

INTRODUCTION: Significant blood loss (≥ 500 mL) during spinal surgery is common and linked to greater transfusion requirements and worse outcomes. Preoperative tools for risk stratification and individualized blood-management strategies are lacking. We aimed to develop a machine-learning model predicting intraoperative significant blood loss and to assess whether a risk-adapted blood management im...

Development and validation of predictive models for prognostic assessment in patients with acute non-ST-segment elevation myocardial infarction: a multicentre real-world study from China.

BACKGROUND: Few models specifically predict the prognoses of non-ST-segment elevation myocardial infarction (NSTEMI) patients. Additionally, these mod...

Deep-Learning Tool ScVital Enables Species-Agnostic Integration of Cancer Cell States.

UNLABELLED: Genetically engineered mouse models (GEMM) of cancer are useful for exploring the development and biological composition of human tumors. ...

Machine Learning Methods to Identify Pediatric Shunt Malfunction in the Acute Care Setting and the Development of ShuntGPT.

BACKGROUND AND OBJECTIVES: Identifying predictors of shunt failure in acute care settings is challenging. Previous studies largely rely on traditional...

Machine learning-predicted insulin resistance is a risk factor for 12 types of cancer.

Insulin resistance is suggested to be a risk factor for cancer; however, large-scale epidemiological evidence linking insulin resistance to cancer rem...

Essential Updates 2024-2025: Surgical Strategy for Esophageal Cancer Toward a New Paradigm in the Era of Immunotherapy and Personalization.

Esophageal cancer surgery is evolving from technical standardization to a paradigm of personalized, strategy-oriented care. Robotic-assisted technique...

Development and external validation of a machine learning model for predicting in-hospital mortality in acute liver failure.

BACKGROUND: Acute liver failure (ALF) is a rapidly progressive and life-threatening condition that requires accurate risk stratification. Existing pro...

Interpretable prognostic modeling of glioblastoma using cross-cohort transcriptome integration and machine learning approaches.

Glioblastoma (GBM) is an aggressive brain tumor with highly variable patient outcomes due to pronounced molecular heterogeneity. Prognosis remains dis...

Machine Learning and Computer Simulation Disentangle the Fuzzy Inhibitor Binding by Hsp90.

Heat shock protein 90 (Hsp90) is a key cancer drug target, yet the highly flexible N-terminal ATP-binding pocket yields seemingly conflicting crystall...

Automatic Detection of Subcellular-Scale Metabolic Dynamics via Spontaneous-Stimulated Raman Spatial Colocalization.

Cellular structural heterogeneity and low intrinsic contrast in label-free bright-field imaging hinder accurate localization of subcellular structures...

Early Risk Factor Prediction in Chronic Kidney Disease Diagnosis Using Feature Selection and Machine Learning Algorithms.

Chronic kidney disease, CKD in short, is a kind of long-term kidney illness in which rapid deterioration of kidney function is observed over a period ...

Development and Validation of a Computational Histology Artificial Intelligence-Powered Predictive Biomarker for Selection of Chemotherapy in Advanced Pancreatic Cancer.

PURPOSE: Predictive biomarkers to guide selection of first-line chemotherapy for advanced pancreatic ductal adenocarcinoma (PDAC) are an unmet clinica...

Preoperative lymphocyte signature predicts pancreatic fistula after pancreatoduodenectomy.

BACKGROUND: Postoperative pancreatic fistula (POPF) is the major driver of postoperative morbidity after pancreatoduodenectomy (PD) and a healthcare i...

Limitation of existing GFR estimating equations and application of artificial intelligence in improving GFR estimation and chronic kidney disease progression in people with diabetes.

The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2009 equation is the most commonly used equation for estimating glomerular filtration ...

A systems approach identifies MERTK as a therapeutic vulnerability in ZFTA-RELA-driven ependymomas.

Ependymomas (EPN) are rare central nervous system tumors that account for approximately 10% of intracranial tumors in children and 4% in adults. Despi...

Development and validation of a prognosis model for low-grade gliomas based on metabolic gene risk scoring and immune microenvironment interaction.

PURPOSE: Low-grade gliomas(LGGs) show significant clinical and molecular heterogeneity, complicating progression prediction with conventional indicato...

A machine learning model for accurate prediction of CMV end-organ disease.

BACKGROUND: Cytomegalovirus (CMV) End-Organ Disease (EOD) remains a significant complication in immunocompromised individuals, particularly transplant...

Deep Learning Identification of Clear Cell Renal Cell Carcinoma on MR Imaging.

OBJECTIVE: To investigate the performance of various convolutional neural networks (CNNs) in identifying clear renal cell carcinoma (ccRCC) on MRI and...

Real-world evaluation of large language models in detecting drug-related problems: A clinical pharmacist-AI concordance study in hematology care.

IntroductionLarge language models (LLMs) offer potential as clinical decision support systems (CDSS) for detecting drug-related problems (DRPs), yet t...