Other Cancers

A gastric cancer LncRNAs model for MSI and survival prediction based on support vector machine.

BACKGROUND: Recent studies have shown that long non-coding RNAs (lncRNAs) play a crucial role in the...

Deep Convolutional Neural Network-based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs.

Background Multicenter studies are required to validate the added benefit of using deep convolutiona...

Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer.

OBJECTIVE: To develop and evaluate the performance of U-Net for fully automated localization and seg...

Multifunctional Nanorobot System for Active Therapeutic Delivery and Synergistic Chemo-photothermal Therapy.

Nanorobots are safe and exhibit powerful functionalities, including delivery, therapy, and diagnosis...

Novel approaches for glioblastoma treatment: Focus on tumor heterogeneity, treatment resistance, and computational tools.

BACKGROUND: Glioblastoma (GBM) is a highly aggressive primary brain tumor. Currently, the suggested ...

Non-invasive diagnosis of non-alcoholic steatohepatitis and fibrosis with the use of omics and supervised learning: A proof of concept study.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) affects 25-30% of the general population and i...

The feasibility of developing biomarkers from peripheral blood mononuclear cell RNAseq data in children with juvenile idiopathic arthritis using machine learning approaches.

BACKGROUND: The response to treatment for juvenile idiopathic arthritis (JIA) can be staged using cl...

Artificial intelligence and big data facilitated targeted drug discovery.

Different kinds of biological databases publicly available nowadays provide us a goldmine of multidi...

Utilizing Machine Learning for Pre- and Postoperative Assessment of Patients Undergoing Resection for BCLC-0, A and B Hepatocellular Carcinoma: Implications for Resection Beyond the BCLC Guidelines.

BACKGROUND: There is an ongoing debate about expanding the resection criteria for hepatocellular car...

Clear cell renal cell carcinoma: Machine learning-based computed tomography radiomics analysis for the prediction of WHO/ISUP grade.

PURPOSE: To evaluate the performance of machine learning (ML)-based computed tomography (CT) radiomi...

Current and future applications of machine and deep learning in urology: a review of the literature on urolithiasis, renal cell carcinoma, and bladder and prostate cancer.

PURPOSE: The purpose of the study was to provide a comprehensive review of recent machine learning (...

ASO Author Reflections: Resection for Hepatocellular Carcinoma Beyond the BCLC Guidelines-How Can Machine Learning Techniques Help?

A method for the automated classification of benign and malignant masses on digital breast tomosynthesis images using machine learning and radiomic features.

In digital mammography, which is used for the early detection of breast tumors, oversight may occur ...

Machine Learning to Predict Anti-Tumor Necrosis Factor Drug Responses of Rheumatoid Arthritis Patients by Integrating Clinical and Genetic Markers.

OBJECTIVE: Accurate prediction of treatment responses in rheumatoid arthritis (RA) patients can prov...

Integration of convolutional neural networks for pulmonary nodule malignancy assessment in a lung cancer classification pipeline.

The early identification of malignant pulmonary nodules is critical for a better lung cancer prognos...

Poly(ethylene glycol)-poly(ε-caprolactone)-based micelles for solubilization and tumor-targeted delivery of silibinin.

Silibinin is a naturally occurring compound with known positive impacts on prevention and treatment...

Diagnosis of Benign and Malignant Breast Lesions on DCE-MRI by Using Radiomics and Deep Learning With Consideration of Peritumor Tissue.

BACKGROUND: Computer-aided methods have been widely applied to diagnose lesions detected on breast M...

Robot-assisted Nipple-sparing Mastectomy with Immediate Breast Reconstruction: An Initial Experience.

Seeking smaller and indistinct incisions, physicians have attempted endoscopic breast surgery in bre...

A 3D Probabilistic Deep Learning System for Detection and Diagnosis of Lung Cancer Using Low-Dose CT Scans.

We introduce a new computer aided detection and diagnosis system for lung cancer screening with low-...

Toward Automated Bladder Tumor Stratification Using Confocal Laser Endomicroscopy.

Urothelial carcinoma of the bladder (UCB) is the most common urinary cancer. White-light cystoscopy...

A hierarchical sequential neural network with feature fusion for sleep staging based on EOG and RR signals.

OBJECTIVE: Currently, the automatic sleep staging methods mainly face two problems: the first proble...