Oncology/Hematology

A Linear Regression and Deep Learning Approach for Detecting Reliable Genetic Alterations in Cancer Using DNA Methylation and Gene Expression Data.

DNA methylation change has been useful for cancer biomarker discovery, classification, and potential...

Classification of cervical neoplasms on colposcopic photography using deep learning.

Colposcopy is widely used to detect cervical cancers, but experienced physicians who are needed for ...

Artificial neural network model for preoperative prediction of severe liver failure after hemihepatectomy in patients with hepatocellular carcinoma.

BACKGROUND: Posthepatectomy liver failure is a worrisome complication after major hepatectomy for he...

Real-time assessment of video images for esophageal squamous cell carcinoma invasion depth using artificial intelligence.

BACKGROUND: Although optimal treatment of superficial esophageal squamous cell carcinoma (SCC) requi...

Deep learning and level set approach for liver and tumor segmentation from CT scans.

PURPOSE: Segmentation of liver organ and tumors from computed tomography (CT) scans is an important ...

MRI-Based Deep-Learning Model for Distant Metastasis-Free Survival in Locoregionally Advanced Nasopharyngeal Carcinoma.

BACKGROUND: Distant metastasis is the primary cause of treatment failure in locoregionally advanced ...

ASO Author Reflections: Development and Validation of a Novel Risk Score Using Machine-Learning Methodology to Predict Recurrence After Hepatectomy for Colorectal Liver Metastases.

A machine learning approach identified a diagnostic model for pancreatic cancer through using circulating microRNA signatures.

Late diagnosis of pancreatic cancer (PC) due to the limited effectiveness of modern testing approach...

Rule-based automatic diagnosis of thyroid nodules from intraoperative frozen sections using deep learning.

Frozen sections provide a basis for rapid intraoperative diagnosis that can guide surgery, but the d...

Technical Note: Deep Learning approach for automatic detection and identification of patient positioning devices for radiation therapy.

PURPOSE: Automatic detection and identification of setup devices, using a deep convolutional neural ...

Editorial for: "Primary Central Nervous System Lymphoma: Clinical Evaluation of Automated Segmentation on Multiparametric MRI Using Deep Learning".

A machine learning framework to trace tumor tissue-of-origin of 13 types of cancer based on DNA somatic mutation.

Carcinoma of unknown primary (CUP), defined as metastatic cancers with unknown cancer origin, occurs...

Radiomics and "radi-…omics" in cancer immunotherapy: a guide for clinicians.

In recent years the concept of precision medicine has become a popular topic particularly in medical...

Automatic Detection Method for Cancer Cell Nucleus Image Based on Deep-Learning Analysis and Color Layer Signature Analysis Algorithm.

Exploring strategies to treat cancer has always been an aim of medical researchers. One of the avail...

Identifying sarcopenia in advanced non-small cell lung cancer patients using skeletal muscle CT radiomics and machine learning.

BACKGROUND: Sarcopenia has been confirmed as a poor prognostic indicator of lung cancer. However, th...

Integrating multi-omics data by learning modality invariant representations for improved prediction of overall survival of cancer.

Breast and ovarian cancers are the second and the fifth leading causes of cancer death among women. ...

Assessment of Magnetic Liposomal Paclitaxel Nanoparticles as a Potential Carrier for the Treatment of Ovarian Cancer.

This study aimed to evaluate the role of magnetic liposome nanoparticles (ML NPs) as a carrier for ...

Multicenter Multireader Evaluation of an Artificial Intelligence-Based Attention Mapping System for the Detection of Prostate Cancer With Multiparametric MRI.

The purpose of this study was to evaluate in a multicenter dataset the performance of an artificial...

Breast Cancer Histopathology Image Classification Using an Ensemble of Deep Learning Models.

Breast cancer is one of the major public health issues and is considered a leading cause of cancer-r...

Breast cancer detection from biopsy images using nucleus guided transfer learning and belief based fusion.

BACKGROUND AND OBJECTIVE: Breast cancer is a frequently diagnosed cancer in women, contributing to s...

Classifying Breast Cancer Subtypes Using Deep Neural Networks Based on Multi-Omics Data.

With the high prevalence of breast cancer, it is urgent to find out the intrinsic difference between...