Hematology

Lymphoma

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

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Augmented deep learning model for improved quantitative accuracy of MR-based PET attenuation correction in PSMA PET-MRI prostate imaging.

PURPOSE: Estimation of accurate attenuation maps for whole-body positron emission tomography (PET) i...

An Intelligent Non-Invasive Real-Time Human Activity Recognition System for Next-Generation Healthcare.

Human motion detection is getting considerable attention in the field of Artificial Intelligence (AI...

Assessing the Scope and Predictors of Intentional Dose Non-adherence in Clinical Trials.

BACKGROUND: Although there is broad agreement that the accurate estimation of non-adherence rates in...

IGRNet: A Deep Learning Model for Non-Invasive, Real-Time Diagnosis of Prediabetes through Electrocardiograms.

The clinical symptoms of prediabetes are mild and easy to overlook, but prediabetes may develop into...

Convolutional Neural Networks in Predicting Nodal and Distant Metastatic Potential of Newly Diagnosed Non-Small Cell Lung Cancer on FDG PET Images.

The purpose of this study was to assess, by analyzing features of the primary tumor with F-FDG PET,...

Comparison of deep learning models for natural language processing-based classification of non-English head CT reports.

PURPOSE: Natural language processing (NLP) can be used for automatic flagging of radiology reports. ...

TooT-T: discrimination of transport proteins from non-transport proteins.

BACKGROUND: Membrane transport proteins (transporters) play an essential role in every living cell b...

Artificial Intelligence Analysis of Gene Expression Data Predicted the Prognosis of Patients with Diffuse Large B-Cell Lymphoma.

OBJECTIVE: We aimed to identify new biomarkers in Diffuse Large B-cell Lymphoma (DLBCL) using the de...

Combination Strategies for Immune-Checkpoint Blockade and Response Prediction by Artificial Intelligence.

The therapeutic concept of unleashing a pre-existing immune response against the tumor by the applic...

LoAdaBoost: Loss-based AdaBoost federated machine learning with reduced computational complexity on IID and non-IID intensive care data.

Intensive care data are valuable for improvement of health care, policy making and many other purpos...

Automated Detection and Grading of Non-Muscle-Invasive Urothelial Cell Carcinoma of the Bladder.

Accurate grading of non-muscle-invasive urothelial cell carcinoma is of major importance; however, h...

GOMCL: a toolkit to cluster, evaluate, and extract non-redundant associations of Gene Ontology-based functions.

BACKGROUND: Functional enrichment of genes and pathways based on Gene Ontology (GO) has been widely ...

The optimized algorithm based on machine learning for inverse kinematics of two painting robots with non-spherical wrist.

This paper studies the inverse kinematics of two non-spherical wrist configurations of painting robo...

DeepMILO: a deep learning approach to predict the impact of non-coding sequence variants on 3D chromatin structure.

Non-coding variants have been shown to be related to disease by alteration of 3D genome structures. ...

Identification of Non-Small Cell Lung Cancer Sensitive to Systemic Cancer Therapies Using Radiomics.

PURPOSE: Using standard-of-care CT images obtained from patients with a diagnosis of non-small cell ...

Distinguishing drug/non-drug-like small molecules in drug discovery using deep belief network.

The advent of computational methods for efficient prediction of the druglikeness of small molecules ...

Using Artificial Intelligence to Detect COVID-19 and Community-acquired Pneumonia Based on Pulmonary CT: Evaluation of the Diagnostic Accuracy.

Background Coronavirus disease 2019 (COVID-19) has widely spread all over the world since the beginn...

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