Oncology/Hematology

Identification and predictive machine learning models construction of gut microbiota associated with lymph node metastasis in colorectal cancer.

This study focuses on the significant role between gut microbiota and lymph node metastasis (LNM) in...

Evaluating cell-free DNA integrity index as a non-invasive biomarker for neoadjuvant chemotherapy in colorectal cancer patients.

BACKGROUND: Neoadjuvant chemotherapy (NAC) is gaining attention as a treatment for advanced colorect...

Recent advances of engineering cell membranes for nanomedicine delivery across the blood-brain barrier.

The blood-brain barrier (BBB) poses a major challenge to the effective delivery of therapeutic agent...

Combining the NanaPPI Toolbox and AI-Driven Virtual Inhibitor Screening for the p53-MDM2 Interaction.

High-throughput screening for inhibitors of protein-protein interactions (PPIs) provides vital infor...

Corrigendum to 'CT-Based Deep Learning Predicts Prognosis in Esophageal Squamous Cell Cancer Patients Receiving Immunotherapy Combined with Chemotherapy' [Acad Radiol 32/6 (2025) 3397-3409].

Deep Learning Model Based on Dual-energy CT for Assessing Cervical Lymph Node Metastasis in Oral Squamous Cell Carcinoma.

BACKGROUND: Accurate detection of lymph node metastasis (LNM) in oral squamous cell carcinoma (OSCC)...

Efficient Ultrasound Breast Cancer Detection with DMFormer: A Dynamic Multiscale Fusion Transformer.

OBJECTIVE: To develop an advanced deep learning model for accurate differentiation between benign an...

Dynamic abdominal MRI image generation using cGANs: A generalized model for various breathing patterns with extensive evaluation.

Organ motion is a limiting factor during the treatment of abdominal tumors. During abdominal interve...

Whole‑exome evolutionary profiling of osteosarcoma uncovers metastasis‑related driver mutations and generates an independently validated predictive classifier.

BACKGROUND: Osteosarcoma is the most common primary malignant bone tumor, with high invasiveness and...

Multilayer perceptron deep learning radiomics model based on Gd-BOPTA MRI to identify vessels encapsulating tumor clusters in hepatocellular carcinoma: a multi-center study.

OBJECTIVES: The purpose of this study is to mainly develop a predictive model based on clinicoradiol...

Explainable machine learning model for predicting the transarterial chemoembolization response and subtypes of hepatocellular carcinoma patients.

Multi-omics analysis of the effects of pla2g4a on the prognosis of various cancers and its experimental validation in breast cancer cell lines.

BACKGROUND: Platelet-related exosomes (PREs) are microparticles secreted by platelets into the blood...

Retraction Note: A combined microfluidic deep learning approach for lung cancer cell high throughput screening toward automatic cancer screening applications.

AG-MS3D-CNN multiscale attention guided 3D convolutional neural network for robust brain tumor segmentation across MRI protocols.

Accurate segmentation of brain tumors from multimodal Magnetic Resonance Imaging (MRI) plays a criti...

An enhanced fusion of transfer learning models with optimization based clinical diagnosis of lung and colon cancer using biomedical imaging.

Lung and colon cancers (LCC) are among the foremost reasons for human death and disease. Early analy...

Automated cell annotation and classification on histopathology for spatial biomarker discovery.

Histopathology with hematoxylin and eosin (H&E) staining is routinely employed for clinical diagnose...

Machine learning-assisted high-throughput prediction and experimental validation of high-responsivity extreme ultraviolet detectors.

Identifying materials with optimal optoelectronic properties for targeted applications represents bo...

AQP9 and IFITM1 as drivers of immune infiltration and tumor progression in IBD-associated colorectal cancer: from computational insights to experimental validation.

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract as...

pyDOSEIA: A Python Package for Radiological Impact Assessment during Long-term or Accidental Atmospheric Releases.

pyDOSEIA is a Python package designed for meteorological data processing and radiological impact ass...

From combination early detection to multicancer testing: shifting cancer care toward proactive prevention and interception.

Identifying the presence of tumors at a very early stage or deciphering the process underlying their...

Shape matters: inferring the motility of confluent cells from static images.

Cell motility in dense cell collectives is pivotal in various diseases like cancer metastasis and as...