Oncology/Hematology

Educational Impact of a National Training Webinar on AI-based Automatic Contouring in Radiation Oncology.

Quantification of Ki-67 labeling index in pediatric brain tumor immunohistochemistry images.

Quantification of the Kiel 67 (Ki-67) labeling index (LI) is critical for assessing proliferation and prognosis in tumors but manual scoring remains a common practice. We present an automated framework for Ki-67 scoring in whole slide images (WSIs) developed for research settings using an Apache Groovy code script for QuPath and complemented by a Python postprocessing script that provides cell den...

AGPAT3 reshapes tumor cell vulnerability to IFNγ-mediated ferroptosis and enhances immunotherapy efficacy through lipid remodeling.

BACKGROUND: Ferroptosis plays a critical role in immune regulation and tumor microenvironment remodeling. However, its therapeutic potential in enhanc...

[Discovery of multi-omics-based biomarkers for immune-related adverse events: precision management with 3D-SPACE].

This article provides a systematic review of the advances in the precise diagnosis and management of immune-related adverse events (irAEs) induced by ...

Accuracy and reproducibility of tumor size measurement using a deep-learning-based CDSS in resected lung cancer.

PURPOSE: MONCAD LCT is a commercially available deep-learning based clinical decision support system (CDSS) for lung screening CT. The aim of this mul...

Precision immunotherapies for systemic lupus erythematosus: From pathogenic targets to translational horizons.

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disorder in which aberrant B-cell activation, persistent autoantibody production, and...

Predictive biomarkers of response to chimeric antigen receptor (CAR) T-cell therapy for pan-haematologic cancer.

Chimeric antigen receptor (CAR) T-cell therapy holds great promise for patients with cancer, and the identification of predictive biomarkers is crucia...

Hybrid Aquila optimizer-Harris Hawks optimization for CNN hyperparameter tuning in brain tumor classification.

Magnetic resonance imaging (MRI) is hard to categorize properly in terms of interclass similarity, there is data imbalance, and sensitive clinical dec...

Pathology Public Datasets for Artificial Intelligence: A Systematic Review.

Histopathology plays a crucial role in the diagnosis of many diseases, especially cancers, for which the correct classification of tissue samples sign...

Multiphase CT-based deep learning radiomics nomogram models for preoperative WHO/ISUP grading of clear cell renal cell carcinoma: a two-center validation study.

BACKGROUND: Preoperative determination of clear cell renal cell carcinoma (ccRCC) World Health Organization/International Society of Urological Pathol...

CT radiomics of adenocarcinoma of the esophagogastric junction: machine learning-based prediction of perineural invasion status.

SMC4/SMAD3/NF-κB axis drives cervical cancer progression and radioresistance via DNA damage repair and immune modulation.

OBJECTIVE: Cervical cancer remains a significant global health burden, with the molecular determinants of its progression and therapeutic resistance n...

Revolutionizing hepatic fibrosis staging: A machine learning approach combining clinical, biochemical, and microbiome insights.

Non-alcoholic Steatohepatitis (NASH) is a common disease that not only affects adults but has also been seen to affect all ages. This includes young a...

Harnessing the Power of artificial intelligence for clinical trials in cancer.

INTRODUCTION: Cancer research has become increasingly data-intensive, with digital pathology, imaging, and genomic sequencing generating vast, heterog...

Dysbiosis of fecal virome in pediatric Crohn's disease and its dynamic changes during infliximab therapy.

UNLABELLED: The gut virome is an emerging but underexplored component of the human microbiota, especially in pediatric Crohn's disease (CD). This stud...

Effect of a Computer-Aided Device for Detecting Gastric Neoplasms: A Multicenter, Randomized Controlled Trial.

BACKGROUND & AIMS: Evidence about the effect of artificial intelligence (AI) on upper endoscopy in multicenter, randomized controlled trials is lackin...

Development and validation of an interpretable MRI-based multimodal fusion model for predicting lymph node metastasis after neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicenter study.

OBJECTIVE: To develop an interpretable multimodal model that integrates pre-treatment Magnetic resonance imaging (MRI)-based deep learning radiomics (...

A two-step scoring model incorporating visceral-to-subcutaneous fat ratio and systemic immunoinflammatory index for predicting cytokine release syndrome severity in patients with gastric cancer receiving Claudin18.2-targeted CAR-T cell therapy.

Cytokine release syndrome (CRS) greatly impacts survival in patients who undergo chimeric antigen receptor (CAR)-T cell therapy, and the identificatio...

Machine Learning Models for Individualized Osteoradionecrosis Risk Prediction in Head and Neck Cancer.

To develop and validate predictive models for osteoradionecrosis (ORN) after head and neck radiation therapy (RT) using time-to-event data with death ...

Prognostic Significance and Immune Landscape of Migrasome-Related Genes in Pancreatic Cancer.

Pancreatic cancer is characterized by early metastasis and high aggressiveness, highlighting the need for novel molecular biomarkers to improve progno...