Other Cancers

Breast cancer detection and classification in mammogram using a three-stage deep learning framework based on PAA algorithm.

In recent years, deep learning has been used to develop an automatic breast cancer detection and cla...

New endoscopic tools in inflammatory bowel disease.

Endoscopic remission is now considered the ultimate long-term goal for treating inflammatory bowel d...

Attention-based Deep Learning for the Preoperative Differentiation of Axillary Lymph Node Metastasis in Breast Cancer on DCE-MRI.

BACKGROUND: Previous studies have explored the potential on radiomics features of primary breast can...

Ovarian tumor diagnosis using deep convolutional neural networks and a denoising convolutional autoencoder.

Discrimination of ovarian tumors is necessary for proper treatment. In this study, we developed a co...

Prediction Model of Residual Neural Network for Pathological Confirmed Lymph Node Metastasis of Ovarian Cancer.

PURPOSE: We want to develop a model for predicting lymph node status based on positron emission comp...

Editorial for "Attention-based Deep Learning for the Preoperative Differentiation of Axillary Lymph Node Metastasis in Breast Cancer on DCE-MRI".

Gradual Self-Training via Confidence and Volume Based Domain Adaptation for Multi Dataset Deep Learning-Based Brain Metastases Detection Using Nonlocal Networks on MRI Images.

BACKGROUND: Research suggests that treatment of multiple brain metastases (BMs) with stereotactic ra...

Re: Giorgio Gandaglia, Elio Mazzone, Armando Stabile, et al. Prostate-specific Membrane Antigen Radioguided Surgery to Detect Nodal Metastases in Primary Prostate Cancer Patients Undergoing Robot-assisted Radical Prostatectomy and Extended Pelvic Lymph Node Dissection: Results of a Planned Interim Analysis of a Prospective Phase 2 Study. Eur Urol.2022;82:411-18.

Predictive gamma passing rate of 3D detector array-based volumetric modulated arc therapy quality assurance for prostate cancer via deep learning.

To predict the gamma passing rate (GPR) of the three-dimensional (3D) detector array-based volumetri...

A Robust End-to-End Deep Learning-Based Approach for Effective and Reliable BTD Using MR Images.

Detection of a brain tumor in the early stages is critical for clinical practice and survival rate. ...

A Fully Deep Learning Paradigm for Pneumoconiosis Staging on Chest Radiographs.

Pneumoconiosis staging has been a very challenging task, both for certified radiologists and compute...

An Improved Neural Network Based on SENet for Sleep Stage Classification.

Sleep staging is an important step in analyzing sleep quality. Traditional manual analysis by psycho...

MLRD-Net: 3D multiscale local cross-channel residual denoising network for MRI-based brain tumor segmentation.

The precise segmentation of multimodal MRI images is the primary stage of tumor diagnosis and treatm...

Deep learning-based automated quantification of goblet cell mucus using histological images as a predictor of clinical relapse of ulcerative colitis with endoscopic remission.

BACKGROUND: Mucin depletion is one of the histological indicators of clinical relapse among patients...

Computer-Vision-Based Dielectrophoresis Mobility Tracking for Characterization of Single-Cell Biophysical Properties.

Fast and precise measurements of live single-cell biophysical properties is significant in disease d...

Deep Learning for Chondrogenic Tumor Classification through Wavelet Transform of Raman Spectra.

The grading of cancer tissues is still one of the main challenges for pathologists. The development ...

Artificial intelligence in pancreatic cancer.

Pancreatic cancer is the deadliest disease, with a five-year overall survival rate of just 11%. The ...

Automatic Liver Tumor Segmentation on Dynamic Contrast Enhanced MRI Using 4D Information: Deep Learning Model Based on 3D Convolution and Convolutional LSTM.

OBJECTIVE: Accurate segmentation of liver tumors, which could help physicians make appropriate treat...

Integrative Histology-Genomic Analysis Predicts Hepatocellular Carcinoma Prognosis Using Deep Learning.

Cancer prognosis analysis is of essential interest in clinical practice. In order to explore the pro...

Implementation of machine learning in the clinic: challenges and lessons in prospective deployment from the System for High Intensity EvaLuation During Radiation Therapy (SHIELD-RT) randomized controlled study.

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) have resulted in significant enth...

Development and validation of a deep learning signature for predicting lymph node metastasis in lung adenocarcinoma: comparison with radiomics signature and clinical-semantic model.

OBJECTIVE: To develop and validate a deep learning (DL) signature for predicting lymph node (LN) met...