Oncology/Hematology

AI-Quantified ¹¹C-MET PET/CT bone marrow metabolic activity for prognostic assessment in newly diagnosed multiple myeloma.

PURPOSE: To develop and validate an AI method for automated quantification of whole-skeleton bone marrow (BM) metabolic activity using Carbon 11 (11C)-methionine (MET) PET/CT and to evaluate its prognostic value compared with Fluorine 18 (18F)-fluorodeoxyglucose (FDG) PET/CT in patients with newly diagnosed MM. METHODS: This prospective study included 49 patients (median age, 68 years; 29 males) w...

Predictive imaging in abdominal oncology: current trends and future directions.

While the concept of predictive imaging is not entirely new, advanced analytic tools such as radiomics and machine learning have laid the foundation for a new generation of predictive imaging, which goes far beyond what is visible to the human eye. Predictive imaging has emerged as a transformative tool in abdominal oncology, offering the potential to personalize cancer detection and diagnosis, st...

Progressive fusion networks with adaptive graph structure learning for cancer subtype classification.

Classifying cancer subtypes is crucial for clinical diagnosis and therapy. Recently, graph neural network (GNN)-based methods have been explored for t...

Integrated multi-task learning framework for hepatocellular carcinoma segmentation and histological grading using fused multi-phase MRI.

OBJECTIVE: This study aims to develop and validate an integrated multi-task framework for hepatocellular carcinoma analysis by combining deep learning...

Development of a room temperature phosphorescence methodology to evaluate the interaction of AI-designed peptides with the tumor biomarker 5-hydroxyindoleacetic acid.

Early detection of neuroendocrine tumors (NETs) is crucial for early and effective intervention, thus reducing the likelihood of tumor progression and...

Xception Convolutional Deep Maxout Network for Enhanced Breast Cancer Classification Using Histopathological Images.

Globally, breast cancer represents the leading cancer type, with millions of women impacted annually. The success of breast cancer treatment relies he...

Cervical cancer in the modern era: cutting-edge strategies for diagnosis and treatment.

Cervical cancer remains a major cause of mortality among women worldwide, highlighting the need for advances in diagnostic and therapeutic strategies....

Using precision medicine methods to identify disease stages for chronic limb-threatening ischemia in participants of the BEST-CLI trial.

BACKGROUND: Chronic limb-threatening ischemia (CLTI), the most severe form of peripheral artery disease, is associated with a high risk of limb loss. ...

LCMF-Net: A lightweight collaborative multimodal fusion network for brain tumor segmentation.

Accurate brain tumor segmentation plays a pivotal role in clinical decision-making, providing essential support for disease screening, treatment plann...

Machine learning-based integration develops a lactate metabolism related gene signature for improving outcomes in pancreatic ductal adenocarcinoma.

OBJECTIVES: Given its high global mortality rate, pancreatic ductal adenocarcinoma (PDAC) remains a significant area of investigation. However, a robu...

Harnessing Artificial Intelligence in Head and Neck Oncology Practice: Data, Diagnosis, and Therapy.

Artificial intelligence (AI) has emerged as a transformative tool across the various domains of head and neck oncology. From early screening and risk ...

Comprehensive multi-omics data to construct hepatocellular carcinoma pathway subtypes and classification model.

The high heterogeneity of Hepatocellular Carcinoma (HCC) severely hampers clinical outcomes. Current classifications based on gene expression profiles...

Development of a selectively AURKB targeting peptide degradation drug with artificial intelligence-assisted design for the treatment of acute lymphoblastic leukemia.

INTRODUCTION: Acute lymphoblastic leukemia (ALL) is a highly heterogeneous hematologic malignancy with poor prognosis in refractory and relapsed cases...

CSF1R and macrophage infiltration: Integrated magnetic resonance imaging radiomics and deep learning-driven models for the preoperative assessment of glioma.

BACKGROUND: Colony-stimulating factor-1 receptor (CSF1R) signaling is crucial for the ability of tumor-associated macrophages (TAMs) to establish an i...

Magnetic resonance imaging-based artificial intelligence model predicts neoadjuvant therapy response in triple-negative breast cancer.

PURPOSE: Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited treatment options and poorer overall survival tha...

NHOC/NHOP as novel biomarkers for predicting lymph node metastasis in NSCLC using PET/CT radiomics and machine learning: a two-center retrospective study.

PURPOSE: NHOC and NHOP, defined as the normalized distances from peak uptake to tumour centroid and perimeter, are novel PET/CT metrics of tumour aggr...

Long-Term Survival and Beneficiaries of Adjuvant Anti-PD-1 Therapy in Resected Hepatocellular Carcinoma.

BACKGROUND: Early and late hepatocellular carcinoma (HCC) recurrences, which are driven by residual and de novo tumors, respectively, differ in biolog...

Enhanced magnetic hyperthermia in graphene-magnetite nanohybrids for cancer therapy: Artificial intelligence-driven validation via Nonlinear Autoregressive with Exogenous Inputs-Long Short-Term Memory (NARX-LSTM) forecasting.

Magnetic hyperthermia offers targeted cancer therapy using alternating magnetic fields (AMFs) to heat nanoparticles. This study evaluates graphene-mag...

Histopathology-based Artificial Intelligence Algorithms for the Prediction of Prostate Cancer Metastasis After Radical Prostatectomy.

BACKGROUND AND OBJECTIVE: Multimodal artificial intelligence (AI) algorithms have been validated to predict prostate cancer (PCa) metastasis using com...

Deep ensemble model with blockchain technology for lung cancer detection with secured data sharing.

Lung cancer is one of the leading causes of cancer-related mortality globally, primarily due to the high frequency of late-stage diagnoses. While exis...