Other Cancers

Radiomic Model Associated with Tumor Microenvironment Predicts Immunotherapy Response and Prognosis in Patients with Locoregionally Advanced Nasopharyngeal Carcinoma.

No robust biomarkers have been identified to predict the efficacy of programmed cell death protein 1 (PD-1) inhibitors in patients with locoregionally advanced nasopharyngeal carcinoma (LANPC). We aimed to develop radiomic models using pre-immunotherapy MRI to predict the response to PD-1 inhibitors and the patient prognosis. This study included 246 LANPC patients (training cohort, = 117; exter...

Clinical benefits of deep learning-assisted ultrasound in predicting lymph node metastasis in pancreatic cancer patients.

AIM: This study aimed to develop and validate a deep learning radiomics nomogram (DLRN) derived from ultrasound images to improve predictive accuracy for lymph node metastasis (LNM) in pancreatic cancer (PC) patients.

Development of the treatment prediction model in the artificial intelligence in depression - medication enhancement study.

We introduce an artificial intelligence model to personalize treatment in major depression, which was deployed in the Artificial Intelligence in Depre...

Palmitoylation regulators drive the progression of clear cell renal cell carcinoma through Inhibition of cuproptosis: insights into the role of ZDHHC18.

BACKGROUND: Protein palmitoylation is a reversible post-translational modification that increases protein hydrophobicity, which can affect protein loc...

[Incidental pulmonary nodules on CT imaging: what to do?].

Incidental pulmonary nodules are very frequently found on CT imaging and may represent (early stage) lung cancers without any signs or symptoms. These...

A model developed by machine learning and principal component analysis for predicting bronchiolitis obliterans syndrome after allogeneic HSCT in a Chinese population with hematologic malignancies.

Bronchiolitis obliterans syndrome (BOS) is a severe pulmonary complication following allogeneic hematopoietic stem cell transplantation (allo-HSCT), w...

MRI Radiomics and Automated Habitat Analysis Enhance Machine Learning Prediction of Bone Metastasis and High-Grade Gleason Scores in Prostate Cancer.

RATIONALE AND OBJECTIVES: To explore the value of machine learning models based on MRI radiomics and automated habitat analysis in predicting bone met...

Hyperspectral Imaging Combined With Deep Learning for Precision Grading of Clear Cell Renal Cell Carcinoma.

This study presents an integrated approach combining hyperspectral imaging (HSI) and deep learning for accurate grading of clear cell renal cell carci...

The impact of artificial intelligence on the endoscopic assessment of inflammatory bowel disease-related neoplasia.

Inflammatory bowel disease (IBD) is a group of chronic inflammatory conditions of the gastrointestinal tract resulting from an inappropriate immune re...

Surveillance and Surgical Salvage Treatment for Endoscopically Removed T1 Colorectal Cancers.

Endoscopic submucosal dissection (ESD) enables en-bloc resection of large lesions more than 20 mm in size. Therefore, the use of ESD has gained broade...

MVKD-Trans: A Multi-View Knowledge Distillation Vision Transformer Architecture for Breast Cancer Classification Based on Ultrasound Images.

Breast cancer is the leading cancer threatening women's health. In recent years, deep neural networks have outperformed traditional methods in terms o...

The diagnostic accuracy of MRI radiomics in axillary lymph node metastasis prediction: a systematic review and meta-analysis.

BACKGROUND: Breast cancer is the most prevalent malignancy in women and a leading cause of mortality. Accurate assessment of axillary lymph node metas...

Generalizable model to predict new or progressing compression fractures in tumor-infiltrated thoracolumbar vertebrae in an all-comer population.

OBJECTIVE: Neurosurgical evaluation is required in the setting of spinal metastases at high risk for leading to a vertebral body fracture. Both irradi...

Algorithm-based intraoperative diagnosis of liver tumors using infrared spectroscopy.

Liver cancer, including hepatocellular carcinoma (HCC), cholangiocellular carcinoma (CCC), and metastases, presents diagnostic challenges during surge...

Assessment of PD-L1 expression and tumour infiltrating lymphocytes in early-stage non-small cell lung carcinoma with artificial intelligence algorithms.

AIMS: To study programmed death ligand 1 (PD-L1) expression and tumour infiltrating lymphocytes (TILs) in patients with early-stage non-small cell lun...

Droplet microfluidics integrated with machine learning reveals how adipose-derived stem cells modulate endocrine response and tumor heterogeneity in ER breast cancer.

Approximately 70% of breast cancer (BC) diagnoses are estrogen receptor positive (ER) with ∼40% of ER BC patients presenting resistance to endocrine ...

Machine Learning-Enhanced Nanoparticle Design for Precision Cancer Drug Delivery.

In recent years, nanomedicine has emerged as a promising approach to deliver therapeutic agents directly to tumors. However, despite its potential, ca...

Artificial intelligence in imaging diagnosis of liver tumors: current status and future prospects.

Liver cancer remains a significant global health concern, ranking as the sixth most common malignancy and the third leading cause of cancer-related de...

Optimized YOLOv8 for enhanced breast tumor segmentation in ultrasound imaging.

Breast cancer significantly affects people's health globally, making early and accurate diagnosis vital. While ultrasound imaging is safe and non-inva...

A fusion-based deep-learning algorithm predicts PDAC metastasis based on primary tumour CT images: a multinational study.

BACKGROUND: Diagnosing the presence of metastasis of pancreatic cancer is pivotal for patient management and treatment, with contrast-enhanced CT scan...