Other Cancers

A Residual Based Attention Model for EEG Based Sleep Staging.

Sleep staging is to score the sleep state of a subject into different sleep stages such as Wake and ...

Artificial intelligence as the next step towards precision pathology.

Pathology is the cornerstone of cancer care. The need for accuracy in histopathologic diagnosis of c...

Alpha Test of Intelligent Machine Learning in Staging Head and Neck Cancer.

Tabu Search and Machine-Learning Classification of Benign and Malignant Proliferative Breast Lesions.

Breast cancer is the most diagnosed cancer among women around the world. The development of computer...

Prostate Cancer Nodal Staging: Using Deep Learning to Predict Ga-PSMA-Positivity from CT Imaging Alone.

Lymphatic spread determines treatment decisions in prostate cancer (PCa) patients. 68Ga-PSMA-PET/CT ...

Pseudo-CT generation from multi-parametric MRI using a novel multi-channel multi-path conditional generative adversarial network for nasopharyngeal carcinoma patients.

PURPOSE: To develop and evaluate a novel method for pseudo-CT generation from multi-parametric MR im...

iLoF: An intelligent Lab on Fiber Approach for Human Cancer Single-Cell Type Identification.

With the advent of personalized medicine, there is a movement to develop "smaller" and "smarter" mic...

Machine Learning Analysis of Image Data Based on Detailed MR Image Reports for Nasopharyngeal Carcinoma Prognosis.

We aimed to assess the use of automatic machine learning (AutoML) algorithm based on magnetic resona...

Hyper-Graph Regularized Constrained NMF for Selecting Differentially Expressed Genes and Tumor Classification.

Non-negative Matrix Factorization (NMF) is a dimensionality reduction approach for learning a parts-...

A comprehensive study on the multi-class cervical cancer diagnostic prediction on pap smear images using a fusion-based decision from ensemble deep convolutional neural network.

The diagnosis of cervical dysplasia, carcinoma in situ and confirmed carcinoma cases is more easily ...

Comparison of statistical machine learning models for rectal protocol compliance in prostate external beam radiation therapy.

PURPOSE: Limiting the dose to the rectum can be one of the most challenging aspects of creating a do...

Automatic Recognition of Laryngoscopic Images Using a Deep-Learning Technique.

OBJECTIVES/HYPOTHESIS: To develop a deep-learning-based computer-aided diagnosis system for distingu...

Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT: external validation and clinical utility for resident training.

PURPOSE: This study aimed to validate a deep learning model's diagnostic performance in using comput...

Predicting individual clinical trajectories of depression with generative embedding.

Patients with major depressive disorder (MDD) show heterogeneous treatment response and highly varia...

Machine Learning Algorithms for Predicting the Recurrence of Stage IV Colorectal Cancer After Tumor Resection.

The aim of this study is to explore the feasibility of using machine learning (ML) technology to pre...

Breast Cancer Classification in Automated Breast Ultrasound Using Multiview Convolutional Neural Network with Transfer Learning.

To assist radiologists in breast cancer classification in automated breast ultrasound (ABUS) imaging...

Application of Machine Learning in Developing a Novelty Five-Pseudogene Signature to Predict Prognosis of Head and Neck Squamous Cell Carcinoma: A New Aspect of "Junk Genes" in Biomedical Practice.

Head and neck squamous cell carcinoma (HNSCC) is the sixth malignancy, which is characterized by poo...

Automated differentiation of benign renal oncocytoma and chromophobe renal cell carcinoma on computed tomography using deep learning.

OBJECTIVES: To develop and evaluate the feasibility of an objective method using artificial intellig...

A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns.

In cancer, the primary tumour's organ of origin and histopathology are the strongest determinants of...

Application of a machine learning algorithm to predict malignancy in thyroid cytopathology.

BACKGROUND: The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) comprises 6 categories ...

Real-time colorectal cancer diagnosis using PR-OCT with deep learning.

Prior reports have shown optical coherence tomography (OCT) can differentiate normal colonic mucosa ...