Other Cancers

Combining radiomics and deep learning features of intra-tumoral and peri-tumoral regions for the classification of breast cancer lung metastasis and primary lung cancer with low-dose CT.

PURPOSE: To investigate the performance of deep learning and radiomics features of intra-tumoral reg...

Real-Time Computer-Aided Detection of Colorectal Neoplasia During Colonoscopy : A Systematic Review and Meta-analysis.

BACKGROUND: Artificial intelligence computer-aided detection (CADe) of colorectal neoplasia during c...

Prediction of central lymph node metastasis based on deep learning models for patients with clinically node-negative papillary thyroid carcinoma.

Evaluating Autoencoders for Dimensionality Reduction of MRI-derived Radiomics and Classification of Malignant Brain Tumors.

Malignant brain tumors including parenchymal metastatic (MET) lesions, glioblastomas (GBM), and lymp...

Predicting Lymph Node Metastasis From Primary Cervical Squamous Cell Carcinoma Based on Deep Learning in Histopathologic Images.

We developed a deep learning framework to accurately predict the lymph node status of patients with ...

Deep learning analysis of mid-infrared microscopic imaging data for the diagnosis and classification of human lymphomas.

The present study presents an alternative analytical workflow that combines mid-infrared (MIR) micro...

Biology-guided deep learning predicts prognosis and cancer immunotherapy response.

Substantial progress has been made in using deep learning for cancer detection and diagnosis in medi...

An overview of ultrasound-derived radiomics and deep learning in liver.

Over the past few years, developments in artificial intelligence (AI), especially in radiomics and d...

Multi-task deep learning-based radiomic nomogram for prognostic prediction in locoregionally advanced nasopharyngeal carcinoma.

PURPOSE: Prognostic prediction is crucial to guide individual treatment for locoregionally advanced ...

Multimodality deep learning radiomics nomogram for preoperative prediction of malignancy of breast cancer: a multicenter study.

. Breast cancer is the most prevalent cancer diagnosed in women worldwide. Accurately and efficientl...

Perioperative and oncological outcomes of robot-assisted laparoscopic partial nephrectomy for cystic and solid renal masses: Evidence from controlled trials.

To evaluate the outcomes of robot-assisted partial nephrectomy (RAPN) for solid and cystic renal tum...

Cytogenetics and genomics in pediatric acute lymphoblastic leukaemia.

The last five decades have witnessed significant improvement in diagnostics, treatment and managemen...

An artificial intelligence-based ecological index for prognostic evaluation of colorectal cancer.

BACKGROUND AND OBJECTIVE: In the tumor microenvironment (TME), the dynamic interaction between tumor...

Automatic detection and classification of lung cancer CT scans based on deep learning and ebola optimization search algorithm.

Recently, research has shown an increased spread of non-communicable diseases such as cancer. Lung c...

Circulating Plasma Exosomal PD-L1 Predicts Prognosis of Head and Neck Squamous Cell Carcinoma After Radiation Therapy.

PURPOSE: Radiation therapy is widely used to treat head and neck squamous cell carcinoma (HNSCC). Th...

Attention-guided multi-scale learning network for automatic prostate and tumor segmentation on MRI.

BACKGROUND AND OBJECTIVE: Image-guided clinical diagnosis can be achieved by automatically and accur...

Global serum profiling: an opportunity for earlier cancer detection.

The advances in cancer research achieved in the last 50 years have been remarkable and have provided...

Deep learning-based radiomics model can predict extranodal soft tissue metastasis in gastric cancer.

BACKGROUND: The potential prognostic value of extranodal soft tissue metastasis (ESTM) has been conf...

Minimally Invasive Robotic Techniques for Hepatocellular Carcinoma Resection: How I Do It.

The adoption of minimally invasive techniques for hepatocellular resection has progressively increas...

Deep Learning for Detecting BRCA Mutations in High-Grade Ovarian Cancer Based on an Innovative Tumor Segmentation Method From Whole Slide Images.

BRCA1 and BRCA2 genes play a crucial role in repairing DNA double-strand breaks through homologous r...

Deep Learning for Predicting Effect of Neoadjuvant Therapies in Non-Small Cell Lung Carcinomas With Histologic Images.

Neoadjuvant therapies are used for locally advanced non-small cell lung carcinomas, whereby patholog...