Oncology/Hematology

A Deep Learning Workflow for Mass-Forming Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma Classification Based on MRI.

OBJECTIVE: Precise classification of mass-forming intrahepatic cholangiocarcinoma (MF-ICC) and hepat...

Application of machine learning techniques for predicting survival in ovarian cancer.

BACKGROUND: Ovarian cancer is the fifth leading cause of mortality among women in the United States....

Raman microspectroscopy and machine learning for use in identifying radiation-induced lung toxicity.

OBJECTIVE: In this work, we explore and develop a method that uses Raman spectroscopy to measure and...

Low-contrast-dose liver CT using low monoenergetic images with deep learning-based denoising for assessing hepatocellular carcinoma: a randomized controlled noninferiority trial.

OBJECTIVE: Low monoenergetic images obtained using noise-reduction techniques may reduce CT contrast...

Deep learning assisted contrast-enhanced CT-based diagnosis of cervical lymph node metastasis of oral cancer: a retrospective study of 1466 cases.

OBJECTIVES: Lymph node (LN) metastasis is a common cause of recurrence in oral cancer; however, the ...

Feasibility study of deep learning-based markerless real-time lung tumor tracking with orthogonal X-ray projection images.

PURPOSE: The feasibility of a deep learning-based markerless real-time tumor tracking (RTTT) method ...

Prostate cancer malignancy detection and localization from mpMRI using auto-deep learning as one step closer to clinical utilization.

Automatic diagnosis of malignant prostate cancer patients from mpMRI has been studied heavily in the...

Deep learning as a new tool in the diagnosis of mycosis fungoides.

Mycosis Fungoides (MF) makes up the most of the cutaneous lymphomas. As a malignant disease, the gre...

An accurate prediction of the origin for bone metastatic cancer using deep learning on digital pathological images.

BACKGROUND: Determining the origin of bone metastatic cancer (OBMC) is of great significance to clin...

The Development of Symbolic Expressions for Fire Detection with Symbolic Classifier Using Sensor Fusion Data.

Fire is usually detected with fire detection systems that are used to sense one or more products res...

Contrast-Enhanced Ultrasound with Deep Learning with Attention Mechanisms for Predicting Microvascular Invasion in Single Hepatocellular Carcinoma.

RATIONALE AND OBJECTIVES: Prediction of microvascular invasion (MVI) status of hepatocellular carcin...

Development and validation of a machine learning algorithm for predicting diffuse midline glioma, H3 K27-altered, H3 K27 wild-type high-grade glioma, and primary CNS lymphoma of the brain midline in adults.

OBJECTIVE: Preoperative diagnosis of diffuse midline glioma, H3 K27-altered (DMG-A) and midline high...

Artificial intelligence-assisted cholangioscopy of malignant biliary strictures: Changing the paradigm?

Developing Artificial Intelligence Models for Extracting Oncologic Outcomes from Japanese Electronic Health Records.

INTRODUCTION: A framework that extracts oncological outcomes from large-scale databases using artifi...

Mesoscopic description of hippocampal replay and metastability in spiking neural networks with short-term plasticity.

Bottom-up models of functionally relevant patterns of neural activity provide an explicit link betwe...

Detection of Colorectal Adenocarcinoma and Grading Dysplasia on Histopathologic Slides Using Deep Learning.

Colorectal cancer (CRC) is one of the most common types of cancer among men and women. The grading o...

Deep Learning-Based Objective and Reproducible Osteosarcoma Chemotherapy Response Assessment and Outcome Prediction.

Osteosarcoma is the most common primary bone cancer, whose standard treatment includes pre-operative...

Deep learning-based assessment of body composition and liver tumour burden for survival modelling in advanced colorectal cancer.

BACKGROUND: Personalized therapy planning remains a significant challenge in advanced colorectal can...

Robot-assisted segmentectomy for small lung cancer using a radiofrequency identification marker.

Owing to the prevalence of robot-assisted thoracoscopic surgery and the increase in the number of sm...

A clinical and time savings evaluation of a deep learning automatic contouring algorithm.

Automatic contouring algorithms may streamline clinical workflows by reducing normal organ-at-risk (...

Predicting Underestimation of Invasive Cancer in Patients with Core-Needle-Biopsy-Diagnosed Ductal Carcinoma In Situ Using Deep Learning Algorithms.

The prediction of an occult invasive component in ductal carcinoma in situ (DCIS) before surgery is ...