Hematology

Lymphoma

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

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Quality of life after non-nerve-sparing, robot-assisted radical prostatectomy.

OBJECTIVE: To evaluate quality of life (QOL) after non-nerve-sparing, robot-assisted radical prostat...

The impact of thermal insulating materials in heat loss control in smart green buildings using experimental and swarm intelligent analysis.

The efficacy of saving energy standards depends on the ability to anticipate the heat loss of buildi...

Variational quantum algorithm for node embedding.

Quantum machine learning has made remarkable progress in many important tasks. However, the gate com...

The utility of automatic segmentation of kidney MRI in chronic kidney disease using a 3D convolutional neural network.

We developed a 3D convolutional neural network (CNN)-based automatic kidney segmentation method for ...

Development and validation of a CT-based deep learning algorithm to augment non-invasive diagnosis of idiopathic pulmonary fibrosis.

RATIONALE: Non-invasive diagnosis of idiopathic pulmonary fibrosis (IPF) involves identification of ...

Geometric Deep Neural Network Using Rigid and Non-Rigid Transformations for Landmark-Based Human Behavior Analysis.

Deep learning architectures, albeit successful in most computer vision tasks, were designed for data...

Shedding light on the black box of a neural network used to detect prostate cancer in whole slide images by occlusion-based explainability.

Diagnostic histopathology faces increasing demands due to aging populations and expanding healthcare...

Embedding-based terminology expansion via secondary use of large clinical real-world datasets.

A log-likelihood based co-occurrence analysis of ∼1.9 million de-identified ICD-10 codes and related...

Non-Metallic MR-Guided Concentric Tube Robot for Intracerebral Hemorrhage Evacuation.

OBJECTIVE: We aim to develop and evaluate an MR-conditional concentric tube robot for intracerebral ...

TumorDetNet: A unified deep learning model for brain tumor detection and classification.

Accurate diagnosis of the brain tumor type at an earlier stage is crucial for the treatment process ...

Non-inferiority of deep learning ischemic stroke segmentation on non-contrast CT within 16-hours compared to expert neuroradiologists.

We determined if a convolutional neural network (CNN) deep learning model can accurately segment acu...

Comprehensive scientometrics and visualization study profiles lymphoma metabolism and identifies its significant research signatures.

BACKGROUND: There is a wealth of poorly utilized unstructured data on lymphoma metabolism, and scien...

Long-term major adverse liver outcomes in 1,260 patients with non-cirrhotic NAFLD.

BACKGROUND & AIMS: Long-term studies of the prognosis of NAFLD are scarce. Here, we investigated the...

Comparing pentafecta outcomes between nerve sparing and non nerve sparing robot-assisted radical prostatectomy in a propensity score-matched study.

Pentafecta (continence, potency, cancer control, free surgical margins, and no complications) is an ...

Elaborating the potential of Artificial Intelligence in automated CAR-T cell manufacturing.

This paper discusses the challenges of producing CAR-T cells for cancer treatment and the potential ...

The use of artificial intelligence to improve the scientific writing of non-native english speakers.

OBJECTIVE: Scientific writing in English is a daunting task for non-native English speakers. The cha...

Impact of retraining a deep learning algorithm for improving guideline-compliant aortic diameter measurements on non-gated chest CT.

PURPOSE/OBJECTIVE: Reliable detection of thoracic aortic dilatation (TAD) is mandatory in clinical r...

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