Other Cancers

Machine Learning Prediction of Extracapsular Extension in Human Papillomavirus-Associated Oropharyngeal Squamous Cell Carcinoma.

OBJECTIVE: To determine whether machine learning (ML) can predict the presence of extracapsular exte...

Challenge for Diagnostic Assessment of Deep Learning Algorithm for Metastases Classification in Sentinel Lymph Nodes on Frozen Tissue Section Digital Slides in Women with Breast Cancer.

PURPOSE: Assessing the status of metastasis in sentinel lymph nodes (SLNs) by pathologists is an ess...

Study on Urinary Candidate Metabolome for the Early Detection of Breast Cancer.

A metabolomic study for determination of certain urinary metabolomes, 1-methyladenosine (1-MA), 1-me...

Clinical Evaluation of Deep Learning and Atlas-Based Auto-Contouring of Bladder and Rectum for Prostate Radiation Therapy.

PURPOSE: Auto-contouring may reduce workload, interobserver variation, and time associated with manu...

An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm.

Non-small-cell lung cancer (NSCLC) patients often develop bone metastases (BM), and the overall surv...

Machine learning-based CT texture analysis to predict HPV status in oropharyngeal squamous cell carcinoma: comparison of 2D and 3D segmentation.

OBJECTIVE: To compare the CT texture feature reproducibility of 2D and 3D segmentations and their ma...

Concise Polygenic Models for Cancer-Specific Identification of Drug-Sensitive Tumors from Their Multi-Omics Profiles.

In silico models to predict which tumors will respond to a given drug are necessary for Precision On...

Robot-assisted combined pancreatectomy/hepatectomy for metastatic pancreatic acinar cell carcinoma: case report and review of the literature.

Acinar cell carcinoma (ACC) of the pancreas is a rare neoplasm with less aggressive behavior than du...

Evaluation of a deep learning-based computer-aided diagnosis system for distinguishing benign from malignant thyroid nodules in ultrasound images.

PURPOSE: Computer-aided diagnosis (CAD) systems assist in solving subjective diagnosis problems that...

Prognostic prediction of carcinoma by a differential-regulatory-network-embedded deep neural network.

The accurate prognostic prediction is essential for precise diagnosis and treatment of carcinoma. In...

Automatic T Staging Using Weakly Supervised Deep Learning for Nasopharyngeal Carcinoma on MR Images.

BACKGROUND: Recent studies have shown that deep learning can help tumor staging automatically. Howev...

Serum markers improve current prediction of metastasis development in early-stage melanoma patients: a machine learning-based study.

Metastasis development represents an important threat for melanoma patients, even when diagnosed at ...

A deep learning algorithm to detect the presence of basal cell carcinoma on Mohs micrographic surgery frozen sections.

Unsupervised machine learning reveals risk stratifying glioblastoma tumor cells.

A goal of cancer research is to reveal cell subsets linked to continuous clinical outcomes to genera...

Ensemble Deep Learning Model for Multicenter Classification of Thyroid Nodules on Ultrasound Images.

BACKGROUND Thyroid nodules are extremely common and typically diagnosed with ultrasound whether beni...

Deep learning detection of prostate cancer recurrence with F-FACBC (fluciclovine, Axumin®) positron emission tomography.

PURPOSE: To evaluate the performance of deep learning (DL) classifiers in discriminating normal and ...

Deep learning-based survival prediction for multiple cancer types using histopathology images.

Providing prognostic information at the time of cancer diagnosis has important implications for trea...

Robotic right hemicolectomy and partial nephrectomy for synchronous malignancies - a video vignette.

Multi-input deep learning architecture for predicting breast tumor response to chemotherapy using quantitative MR images.

PURPOSE: Neoadjuvant chemotherapy (NAC) aims to minimize the tumor size before surgery. Predicting r...

A machine learning model for detecting invasive ductal carcinoma with Google Cloud AutoML Vision.

OBJECTIVES: This study is aimed to assess the feasibility of AutoML technology for the identificatio...

Deep-Learning F-FDG Uptake Classification Enables Total Metabolic Tumor Volume Estimation in Diffuse Large B-Cell Lymphoma.

Total metabolic tumor volume (TMTV), calculated from F-FDG PET/CT baseline studies, is a prognostic ...