Lymphoma

Deep-learning single-shot detector for automatic detection of brain metastases with the combined use of contrast-enhanced and non-enhanced computed tomography images.

PURPOSE: To develop a deep-learning object detection model for automatic detection of brain metastas...

Predicting response to immunotherapy plus chemotherapy in patients with esophageal squamous cell carcinoma using non-invasive Radiomic biomarkers.

OBJECTIVES: To develop and validate a radiomics model for evaluating treatment response to immune-ch...

Non-Visual Accessibility Assessment of Videos.

Video accessibility is crucial for blind screen-reader users as online videos are increasingly playi...

Enhanced precision of real-time control photothermal therapy using cost-effective infrared sensor array and artificial neural network.

Photothermal therapy (PTT) requires tight thermal dose control to achieve tumor ablation with minima...

Kohonen Network-Based Adaptation of Non Sequential Data for Use in Convolutional Neural Networks.

Convolutional neural networks have become one of the most powerful computing tools of artificial int...

A deep learning- and CT image-based prognostic model for the prediction of survival in non-small cell lung cancer.

OBJECTIVE: To assist clinicians in arranging personalized treatment, planning follow-up programs and...

Single-port Mini-Pfannenstiel Robotic Pyeloplasty: Establishing a Non-narcotic Pathway Along With a Same-day Discharge Protocol.

OBJECTIVE: To analyze the feasibility of a same day discharge protocol following single-port (SP) ro...

Deep Learning for Prediction of N2 Metastasis and Survival for Clinical Stage I Non-Small Cell Lung Cancer.

Background Preoperative mediastinal staging is crucial for the optimal management of clinical stage ...

Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation.

Multi-view clustering has become an active topic in artificial intelligence. Yet, similar investigat...

Artificial intelligence strategy integrating morphologic and architectural biomarkers provides robust diagnostic accuracy for disease progression in chronic lymphocytic leukemia.

Artificial intelligence-based tools designed to assist in the diagnosis of lymphoid neoplasms remain...

Understanding students' evaluations of professors using non-negative matrix factorization.

In this paper, we use Nonnegative Matrix Factorization (NMF) and several other state of the art stat...

Non-transfer Deep Learning of Optical Coherence Tomography for Post-hoc Explanation of Macular Disease Classification.

Deep transfer learning is a popular choice for classifying monochromatic medical images using models...

Effectiveness of Create ML in microscopy image classifications: a simple and inexpensive deep learning pipeline for non-data scientists.

Observing chromosomes is a time-consuming and labor-intensive process, and chromosomes have been ana...

Dynamics and Control of a Magnetic Transducer Array Using Multi-Physics Models and Artificial Neural Networks.

A linear mechanical oscillator is non-linearly coupled with an electromagnet and its driving circuit...

Real-Time Detection of Non-Stationary Objects Using Intensity Data in Automotive LiDAR SLAM.

This article aims at demonstrating the feasibility of modern deep learning techniques for the real-t...

Non-granular laterally spreading tumors: potential superficial cancers that artificial intelligence does not easily detect.

Validation of an artificial intelligence solution for acute triage and rule-out normal of non-contrast CT head scans.

PURPOSE: Non-contrast CT head scans provide rapid and accurate diagnosis of acute head injury; howev...

The Trials and Tribulations of Assembling Large Medical Imaging Datasets for Machine Learning Applications.

With vast interest in machine learning applications, more investigators are proposing to assemble la...

COVID-19 detection from lung CT-Scans using a fuzzy integral-based CNN ensemble.

The COVID-19 pandemic has collapsed the public healthcare systems, along with severely damaging the ...

Retrospective study of deep learning to reduce noise in non-contrast head CT images.

PURPOSE: Presented herein is a novel CT denoising method uses a skip residual encoder-decoder framew...

Outcome-based multiobjective optimization of lymphoma radiation therapy plans.

At its core, radiation therapy (RT) requires balancing therapeutic effects against risk of adverse e...