Other Cancers

Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response.

Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indicat...

ASO Author Reflections: Safety and Feasibility of Robot-Assisted Minimally Invasive Esophagectomy (RAMIE) with Three-Field Lymphadenectomy and Neoadjuvant Chemoradiotherapy in Patients with Resectable Esophageal Cancer and Cervical Lymph Node Metastasis.

SleepPPG-Net: A Deep Learning Algorithm for Robust Sleep Staging From Continuous Photoplethysmography.

Sleep staging is an essential component in the diagnosis of sleep disorders and management of sleep ...

Knowledge Sharing for Pulmonary Nodule Detection in Medical Cyber-Physical Systems.

With the rapid development of edge intelligence (EI) and machine learning (ML), the applications of ...

Nearest Neighbor-Based Strategy to Optimize Multi-View Triplet Network for Classification of Small-Sample Medical Imaging Data.

Multi-view classification with limited sample size and data augmentation is a very common machine le...

Computer-Assisted Diagnosis of Lymph Node Metastases in Colorectal Cancers Using Transfer Learning With an Ensemble Model.

Screening of lymph node metastases in colorectal cancer (CRC) can be a cumbersome task, but it is am...

Deep learning automates bidimensional and volumetric tumor burden measurement from MRI in pre- and post-operative glioblastoma patients.

Tumor burden assessment by magnetic resonance imaging (MRI) is central to the evaluation of treatmen...

Dual parallel net: A novel deep learning model for rectal tumor segmentation via CNN and transformer with Gaussian Mixture prior.

Segmentation of rectal cancerous regions from Magnetic Resonance (MR) images can help doctor define ...

MRI brain tumor segmentation using residual Spatial Pyramid Pooling-powered 3D U-Net.

Brain tumor diagnosis has been a lengthy process, and automation of a process such as brain tumor se...

Convolution Neural Network for Breast Cancer Detection and Classification Using Deep Learning.

OBJECTIVE: Early detection and precise diagnosis of breast cancer (BC) plays an essential part in en...

Improved UNet Deep Learning Model for Automatic Detection of Lung Cancer Nodules.

Uncontrolled cell growth in the two spongy lung organs in the chest is the most prevalent kind of ca...

Predicting origin for bone metastatic cancer using deep learning-based pathology.

Annotation-Free Deep Learning-Based Prediction of Thyroid Molecular Cancer Biomarker BRAF (V600E) from Cytological Slides.

Thyroid cancer is the most common endocrine cancer. Papillary thyroid cancer (PTC) is the most preva...

Safety and Feasibility of Robot-Assisted Minimally Invasive Esophagectomy (RAMIE) with Three-Field Lymphadenectomy and Neoadjuvant Chemoradiotherapy in Patients with Resectable Esophageal Cancer and Cervical Lymph Node Metastasis.

BACKGROUND: In the West, patients with cervical lymph node metastasis of resectable esophageal cance...

Robot-assisted TAMIS: a systematic review of feasibility and outcomes.

BACKGROUND: In the advancement of transanal local excision, robot-assisted transanal minimal invasiv...

MRI-based two-stage deep learning model for automatic detection and segmentation of brain metastases.

OBJECTIVES: To develop and validate a two-stage deep learning model for automatic detection and segm...

Deep learning based identification of bone scintigraphies containing metastatic bone disease foci.

PURPOSE: Metastatic bone disease (MBD) is the most common form of metastases, most frequently derivi...

Quantifying stiffness and forces of tumor colonies and embryos using a magnetic microrobot.

Stiffness and forces are two fundamental quantities essential to living cells and tissues. However, ...

A deep-learning algorithm to localize basal cell carcinoma foci on Mohs surgery frozen sections.

Prediction of malignancy upgrade rate in high-risk breast lesions using an artificial intelligence model: a retrospective study.

PURPOSE: High-risk breast lesions (HRLs) are associated with future risk of breast cancer. Consideri...

A machine learning model for predicting the three-year survival status of patients with hypopharyngeal squamous cell carcinoma using multiple parameters.

OBJECTIVE: This study aimed to establish a model for predicting the three-year survival status of pa...