Oncology/Hematology

Editorial for "Automated Segmentation of Brain Metastases on T1-Weighted MRI Using Convolutional Neural Network: Impact of Using Volume Aware Loss and Sampling Strategy".

Deep learning for image-based liver analysis - A comprehensive review focusing on malignant lesions.

Deep learning-based methods, in particular, convolutional neural networks and fully convolutional ne...

Deep learning based time-to-event analysis with PET, CT and joint PET/CT for head and neck cancer prognosis.

OBJECTIVES: Recent studies have shown that deep learning based on pre-treatment positron emission to...

A deep learning model combining multimodal radiomics, clinical and imaging features for differentiating ocular adnexal lymphoma from idiopathic orbital inflammation.

OBJECTIVES: To evaluate the value of deep learning (DL) combining multimodal radiomics and clinical ...

Editorial Comment: The Future Value of Automated CT-Derived Body Composition in Oncologic Patients.

Deep learning-based transcription factor activity for stratification of breast cancer patients.

Transcription factors directly bind to DNA and regulate the expression of the gene, causing epigenet...

A machine learning model for separating epithelial and stromal regions in oral cavity squamous cell carcinomas using H&E-stained histology images: A multi-center, retrospective study.

OBJECTIVE: Tissue slides from Oral cavity squamous cell carcinoma (OC-SCC), particularly the epithel...

ZhenQi FuZheng formula inhibits the growth of colorectal tumors by modulating intestinal microflora-mediated immune function.

Zhenqi Fuzheng formula (ZQFZ), of which the main ingredients are and , has immune system regulatory...

Deep-learning-based analysis of preoperative MRI predicts microvascular invasion and outcome in hepatocellular carcinoma.

BACKGROUND: Preoperative prediction of microvascular invasion (MVI) is critical for treatment strate...

Deep learning features encode interpretable morphologies within histological images.

Convolutional neural networks (CNNs) are revolutionizing digital pathology by enabling machine learn...

Prediction for Distant Metastasis of Breast Cancer Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging Images under Deep Learning.

This research aimed to explore the effect of using magnetic resonance imaging (MRI) radiomic feature...

Radiomics and artificial intelligence in malignant uterine body cancers: Protocol for a systematic review.

INTRODUCTION: Uterine body cancers (UBC) are represented by endometrial carcinoma (EC) and uterine s...

Artificial Intelligence Algorithm in Classification and Recognition of Primary Hepatic Carcinoma Images under Magnetic Resonance Imaging.

This study aimed to discuss the application value of the bias field correction algorithm in magnetic...

Breast Tumor Detection Using Robust and Efficient Machine Learning and Convolutional Neural Network Approaches.

Breast cancer develops when cells in the breast expand and divide uncontrollably, resulting in a lum...

Hybrid robotic lobectomy with thoracic wall resection for superior sulcus tumor.

A major challenge in treating superior sulcus tumors is achieving complete surgical resection becaus...

Simulating the restoration of normal gene expression from different thyroid cancer stages using deep learning.

BACKGROUND: Thyroid cancer (THCA) is the most common endocrine malignancy and incidence is increasin...

Liver Attenuation Assessment in Reduced Radiation Chest Computed Tomography.

OBJECTIVE: This study aimed to evaluate the reliability of liver and spleen Hounsfield units (HU) me...

DiaDeL: An Accurate Deep Learning-Based Model With Mutational Signatures for Predicting Metastasis Stage and Cancer Types.

Mutational signatures help identify cancer-associated genes that are being involved in tumorigenesis...

The robotic-assisted extended "Sistrunk" approach for tumors of the upper aerodigestive tract with limited transoral access: First description of oncological and functional outcomes.

We report on the first clinical experience with the robotic-assisted extended "Sistrunk" approach (R...

The Masking Impact of Intra-Artifacts in EEG on Deep Learning-Based Sleep Staging Systems: A Comparative Study.

Elimination of intra-artifacts in EEG has been overlooked in most of the existing sleep staging syst...

CT-Derived Body Composition Assessment as a Prognostic Tool in Oncologic Patients: From Opportunistic Research to Artificial Intelligence-Based Clinical Implementation.

CT-based body composition measures are well established in research settings as prognostic markers i...