Lymphoma

Predicting the trajectory of non-suicidal self-injury among adolescents.

BACKGROUND: Non-suicidal self-injury (NSSI) is common among adolescents receiving inpatient psychiat...

Efficient model-informed co-segmentation of tumors on PET/CT driven by clustering and classification information.

Automatic tumor segmentation via positron emission tomography (PET) and computed tomography (CT) ima...

Data-free knowledge distillation via generator-free data generation for Non-IID federated learning.

Data heterogeneity (Non-IID) on Federated Learning (FL) is currently a widely publicized problem, wh...

Non-invasive prediction of axillary lymph node dissection exemption in breast cancer patients post-neoadjuvant therapy: A radiomics and deep learning analysis on longitudinal DCE-MRI data.

PURPOSE: In breast cancer (BC) patients with clinical axillary lymph node metastasis (cN+) undergoin...

A Deep Learning Method for Pneumonia Detection Based on Fuzzy Non-Maximum Suppression.

Pneumonia is one of the largest causes of death in the world. Deep learning techniques can assist do...

Commentary: Detection of Endoleak After Endovascular Aortic Repair Through Deep Learning Based on Non-contrast CT.

Ensemble machine learning to predict futile recanalization after mechanical thrombectomy based on non-contrast CT imaging.

OBJECTIVES: Despite successful recanalization after Mechanical Thrombectomy (MT), approximately 25 %...

Non-Contact Blood Pressure Estimation From Radar Signals by a Stacked Deformable Convolution Network.

This study introduces a contactless blood pressure monitoring approach that combines conventional ra...

A Deep Learning-Based Framework for Predicting Intracerebral Hematoma Expansion Using Head Non-contrast CT Scan.

RATIONALE AND OBJECTIVES: Hematoma expansion (HE) in intracerebral hemorrhage (ICH) is a critical fa...

Integrating knowledge graphs into machine learning models for survival prediction and biomarker discovery in patients with non-small-cell lung cancer.

Accurate survival prediction for Non-Small Cell Lung Cancer (NSCLC) patients remains a significant c...

Optimizing adjuvant treatment strategies for non-pancreatic periampullary cancers.

Non-pancreatic periampullary tumors have long been neglected, leading to blurred adjuvant treatment ...

CT-based deep learning radiomics biomarker for programmed cell death ligand 1 expression in non-small cell lung cancer.

BACKGROUND: Programmed cell death ligand 1 (PD-L1), as a reliable predictive biomarker, plays an imp...

Clinical feasibility of deep learning based synthetic contrast enhanced abdominal CT in patients undergoing non enhanced CT scans.

Our objective was to develop and evaluate the clinical feasibility of deep-learning-based synthetic ...

Multitask learning of a biophysically-detailed neuron model.

The human brain operates at multiple levels, from molecules to circuits, and understanding these com...

Machine learning-derived prognostic signature for progression-free survival in non-metastatic nasopharyngeal carcinoma.

BACKGROUND: Early detection of high-risk nasopharyngeal carcinoma (NPC) recurrence is essential. We ...

The impact of high-order features on performance of radiomics studies in CT non-small cell lung cancer.

High-order radiomic features have been shown to produce high performance models in a variety of scen...

Self-learning neural network as a prediction model in non-invasive prenatal testing to detect fetal SNVs.

Computer-aided prognosis of tuberculous meningitis combining imaging and non-imaging data.

Tuberculous meningitis (TBM) is the most lethal form of tuberculosis. Clinical features, such as com...

Using VIS-NIR hyperspectral imaging and deep learning for non-destructive high-throughput quantification and visualization of nutrients in wheat grains.

High-throughput and low-cost quantification of the nutrient content in crop grains is crucial for fo...

Artificial intelligence assisted ultrasound for the non-invasive prediction of axillary lymph node metastasis in breast cancer.

PURPOSE: A practical noninvasive method is needed to identify lymph node (LN) status in breast cance...

An unrolled neural network for accelerated dynamic MRI based on second-order half-quadratic splitting model.

The reconstruction of dynamic magnetic resonance images from incomplete k-space data has sparked sig...