Other Cancers

Deep Learning-Based Automatic Assessment of Radiation Dermatitis in Patients With Nasopharyngeal Carcinoma.

PURPOSE: Radiation dermatitis (RD) is a common, unpleasant side effect of patients receiving radiati...

Scrutinizing high-risk patients from ASC-US cytology via a deep learning model.

BACKGROUND: Atypical squamous cells of undetermined significance (ASC-US) is the most frequent but a...

Deep learning method with a convolutional neural network for image classification of normal and metastatic axillary lymph nodes on breast ultrasonography.

PURPOSE: To investigate the ability of deep learning (DL) using convolutional neural networks (CNNs)...

Oncological drug discovery: AI meets structure-based computational research.

The integration of machine learning and structure-based methods has proven valuable in the past as a...

Radiomic and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography and Dynamic Contrast Magnetic Resonance Imaging to Detect Breast Malignant Lesions.

:The purpose of this study was to discriminate between benign and malignant breast lesions through s...

Retroperitoneal robot-assisted single-port laparoscopic treatment of the horseshoe kidney with renal cell carcinoma: Report of two cases.

The feasibility study on the generalization of deep learning dose prediction model for volumetric modulated arc therapy of cervical cancer.

PURPOSE: To develop a 3D-Unet dose prediction model to predict the three-dimensional dose distributi...

Long short-term memory model - A deep learning approach for medical data with irregularity in cancer predication with tumor markers.

BACKGROUND: Machine learning (ML) has emerged as a superior method for the analysis of large dataset...

Deep Transfer Learning Approaches in Performance Analysis of Brain Tumor Classification Using MRI Images.

Brain tumor classification is a very important and the most prominent step for assessing life-threat...

iTTCA-MFF: identifying tumor T cell antigens based on multiple feature fusion.

Cancer is a terrible disease, recent studies reported that tumor T cell antigens (TTCAs) may play a ...

Application of High Throughput Technologies in the Development of Acute Myeloid Leukemia Therapy: Challenges and Progress.

Acute myeloid leukemia (AML) is a complex hematological malignancy characterized by extensive hetero...

The association between perineural invasion in mpMRI-targeted and/or systematic prostate biopsy and adverse pathological outcomes in robot-assisted radical prostatectomy.

INTRODUCTION AND OBJECTIVES: This study aims to investigate the relationship between perineural inva...

Robot-Assisted Prostate-Specific Membrane Antigen-Radioguided Surgery in Primary Diagnosed Prostate Cancer.

The objective of this study was to evaluate the safety and feasibility of Tc-based prostate-specific...

The role of artificial intelligence in pancreatic surgery: a systematic review.

Artificial intelligence (AI), including machine learning (ML), is being slowly incorporated in medic...

Human colorectal cancer tissue assessment using optical coherence tomography catheter and deep learning.

Optical coherence tomography (OCT) can differentiate normal colonic mucosa from neoplasia, potential...

Tomographic Ultrasound Imaging in the Diagnosis of Breast Tumors under the Guidance of Deep Learning Algorithms.

This study was aimed to discuss the feasibility of distinguishing benign and malignant breast tumors...

Convolutional neural network is a good technique for sleep staging based on HRV: A comparative analysis.

The fluctuation of heart rate is regulated by autonomic nervous system. In human sleep, the autonomi...

Accelerate treatment planning process using deep learning generated fluence maps for cervical cancer radiation therapy.

PURPOSE: This study aims to develop a deep learning method that skips the time-consuming inverse opt...

Deep learning using bulk RNA-seq data expands cell landscape identification in tumor microenvironment.

The tumor microenvironment (TME) profoundly influences tumor progression and affects immunotherapy r...

Detection and staging of chronic obstructive pulmonary disease using a computed tomography-based weakly supervised deep learning approach.

OBJECTIVES: Chronic obstructive pulmonary disease (COPD) is underdiagnosed globally. The present stu...

Cross-institutional outcome prediction for head and neck cancer patients using self-attention neural networks.

In radiation oncology, predicting patient risk stratification allows specialization of therapy inten...