Hematology

Lymphoma

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

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Simulation-based inference for non-parametric statistical comparison of biomolecule dynamics.

Numerous models have been developed to account for the complex properties of the random walks of bio...

Self-Supervised Learning for Non-Rigid Registration Between Near-Isometric 3D Surfaces in Medical Imaging.

Non-rigid registration between 3D surfaces is an important but notorious problem in medical imaging,...

Correlative Fluorescence and Raman Microscopy to Define Mitotic Stages at the Single-Cell Level: Opportunities and Limitations in the AI Era.

Nowadays, morphology and molecular analyses at the single-cell level have a fundamental role in unde...

Robot-assisted laparoscopic cystectomy with non-continent urinary diversion for neurogenic lower urinary tract dysfunction: Midterm outcomes.

OBJECTIVES: The aim of this study was to assess midterm functional outcomes and complications of rob...

Using deep learning to detect diabetic retinopathy on handheld non-mydriatic retinal images acquired by field workers in community settings.

Diabetic retinopathy (DR) at risk of vision loss (referable DR) needs to be identified by retinal sc...

Non-task expert physicians benefit from correct explainable AI advice when reviewing X-rays.

Artificial intelligence (AI)-generated clinical advice is becoming more prevalent in healthcare. How...

Enhancing System Performance through Objective Feature Scoring of Multiple Persons' Breathing Using Non-Contact RF Approach.

Breathing monitoring is an efficient way of human health sensing and predicting numerous diseases. V...

A radiomics-based deep learning approach to predict progression free-survival after tyrosine kinase inhibitor therapy in non-small cell lung cancer.

BACKGROUND: The epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are a firs...

Using deep learning to predict survival outcome in non-surgical cervical cancer patients based on pathological images.

PURPOSE: We analyzed clinical features and the representative HE-stained pathologic images to predic...

Non-parametric severity-duration-frequency analysis of drought based on satellite-based product and model fusion techniques.

Climate change has increased the severity and frequency of droughts over the last decades. To allevi...

Non-coding deep learning models for tomato biotic and abiotic stress classification using microscopic images.

Plant disease classification is quite complex and, in most cases, requires trained plant pathologist...

Predicting N2 lymph node metastasis in presurgical stage I-II non-small cell lung cancer using multiview radiomics and deep learning method.

BACKGROUND: Accurate diagnosis of N2 lymph node status of the resectable stage I-II non-small cell l...

Non Linear Control System for Humanoid Robot to Perform Body Language Movements.

In social robotics, especially with regard to direct interactions between robots and humans, the rob...

NCSP-PLM: An ensemble learning framework for predicting non-classical secreted proteins based on protein language models and deep learning.

Non-classical secreted proteins (NCSPs) refer to a group of proteins that are located in the extrace...

Convolutional neural network for automated segmentation of the liver and its vessels on non-contrast T1 vibe Dixon acquisitions.

We evaluated the effectiveness of automated segmentation of the liver and its vessels with a convolu...

Cross-species cell-type assignment from single-cell RNA-seq data by a heterogeneous graph neural network.

Cross-species comparative analyses of single-cell RNA sequencing (scRNA-seq) data allow us to explor...

Performance of 1-mm non-gated low-dose chest computed tomography using deep learning-based noise reduction for coronary artery calcium scoring.

OBJECTIVE: To investigate performance of 1-mm, sharp kernel, low-dose chest computed tomography (LDC...

Research on cell detection method for microfluidic single cell dispensing.

Single cell dispensing techniques mainly include limiting dilution, fluorescent-activated cell sorti...

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