Hematology

Lymphoma

Latest AI and machine learning research in lymphoma for healthcare professionals.

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A Non-Linear Body Machine Interface for Controlling Assistive Robotic Arms.

OBJECTIVE: Body machine interfaces (BoMIs) enable individuals with paralysis to achieve a greater me...

Deep Learning-Based Non-Contact IPPG Signal Blood Pressure Measurement Research.

In this paper, a multi-stage deep learning blood pressure prediction model based on imaging photople...

Caffeinated non-alcoholic beverages on the postpartum mental health related to the COVID-19 pandemic by a cross-sectional study in Argentina.

PURPOSE: This work aimed to study postpartum mental outcomes and determinants of the intake of caffe...

Deep learning-based prognostic model using non-enhanced cardiac cine MRI for outcome prediction in patients with heart failure.

OBJECTIVES: To evaluate the performance of a deep learning-based multi-source model for survival pre...

Brain-optimized deep neural network models of human visual areas learn non-hierarchical representations.

Deep neural networks (DNNs) optimized for visual tasks learn representations that align layer depth ...

Iterative Item Selection of Neighborhood Clusters: A Nonparametric and Non-IRT Method for Generating Miniature Computer Adaptive Questionnaires.

The questionnaire method has always been an important research method in psychology. The increasing ...

A deep-learning model using enhanced chest CT images to predict PD-L1 expression in non-small-cell lung cancer patients.

AIM: To develop a deep-learning model using contrast-enhanced chest computed tomography (CT) images ...

Benchmarking physics-informed frameworks for data-driven hyperelasticity.

Data-driven methods have changed the way we understand and model materials. However, while providing...

Enhancement of Non-Linear Deep Learning Model by Adjusting Confounding Variables for Bone Age Estimation in Pediatric Hand X-rays.

In medicine, confounding variables in a generalized linear model are often adjusted; however, these ...

Non-invasive grading of brain tumors using online support vector machine with dynamic fuzzy rule-based parameters optimization.

Non-invasive grading of brain tumors provides a valuable understanding of tumor growth that helps ch...

Diagnosis of Liver Fibrosis Using Artificial Intelligence: A Systematic Review.

The development of liver fibrosis as a consequence of continuous inflammation represents a turning ...

Feasibility of accelerated non-contrast-enhanced whole-heart bSSFP coronary MR angiography by deep learning-constrained compressed sensing.

OBJECTIVES: To examine a compressed sensing artificial intelligence (CSAI) framework to accelerate i...

A Machine Learning Prediction Model for Non-cardiogenic Out-of-hospital Cardiac Arrest with Initial Non-shockable Rhythm.

OBJECTIVES: The purpose of this study was to develop and validate a machine learning prediction mode...

DGA3-Net: A parameter-efficient deep learning model for ASPECTS assessment for acute ischemic stroke using non-contrast computed tomography.

Detecting the early signs of stroke using non-contrast computerized tomography (NCCT) is essential f...

A machine learning model for orthodontic extraction/non-extraction decision in a racially and ethnically diverse patient population.

INTRODUCTION: The purpose of the present study was to create a machine learning (ML) algorithm with ...

Emerging uses of artificial intelligence in breast and axillary ultrasound.

Breast ultrasound is a valuable adjunctive tool to mammography in detecting breast cancer, especiall...

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