Lymphoma

A Predictive Nomogram Integrating AI-Assisted Morphological Feature Extraction with Clinical and Ultrasound Parameters for Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer.

OBJECTIVE: To develop and validate a nomogram integrating artificial intelligence (AI)-extracted ultrasound features with clinic pathologic data for non-invasive preoperative prediction of ipsilateral axillary lymph node (IALN) metastasis in breast cancer women. MATERIALS AND METHODS: This retrospective study, approved by the institutional review board with consent waived, included 148 women (mean...

Mantle cell lymphoma artificial intelligence prognostic index using hematoxylin and eosin histology.

The clinical course of Mantle Cell Lymphoma (MCL) varies between individual patients. Early detection of risk is crucial to assign MCL patients to novel treatment strategies. Most of the established biomarkers of outcome require specifically trained pathologists or molecular analysis. Here we introduce MAIPI (MCL Artificial Intelligence Prognostic Index), a deep learning algorithm trained only on ...

Effects of 5D built environment and non-built-environment factors on injury crash risk: An interpretable machine learning analysis.

To identify the key determinants of traffic injury risk and clarify the relative roles of built environment factors and crash-context factors, this st...

Deep learning-based chemical shift-artifact correction of ZTE MRI for enhanced bone depiction of the lumbar spine.

RATIONALE AND OBJECTIVES: Zero echo time (ZTE) is an advanced MRI technique providing CT-like images of mineralized tissues. This study evaluates the ...

The application of artificial intelligence in adrenal imaging: current state of knowledge, challenges, and future directions.

Adrenal incidentalomas are frequently detected on abdominal imaging and require evaluation for malignancy and hormonal activity. Although most are ben...

Novel Imaging Approaches for Visualising Root-Mycorrhizal Fungal Interactions.

Mycorrhizal fungi form essential symbiotic relationships with plant roots, facilitating nutrient exchange and promoting plant health. Understanding th...

Prediction of Type 2 Diabetes Mellitus From Chest X-Rays Using a Suite of Previously Developed Chronic Disease Deep Learning Models in an Ethnically Diverse Cohort: Observational Study.

BACKGROUND: Screening for type 2 diabetes (T2D) is not optimal, leading to a large number of patients being undiagnosed. Recently, deep learning (DL) ...

Innovation districts and transformative workspaces: A scoping review of AI-pet robots companionship for aging employees balancing productivity and wellbeing.

BACKGROUND: Considering the future of work and an aging workforce, emerging technologies such as artificial intelligence (AI) and robots are promising...

Machine learning-guided discovery of poly(ethylene terephthalate)-binding modules to enhance durable whole-cell degradation.

The enzymatic degradation of poly(ethylene terephthalate) (PET) offers a sustainable route for plastic recycling but is often hindered by limited enzy...

Artificial intelligence-based automated sleep staging using heart rate variability: Assessment of performance and clinical prospects.

Background Some artificial intelligence models use heart rate variability (HRV) features to classify sleep stages. Estimation of HRV indices requires ...

APEX-NET: automated pancreatic evaluation network using early non-contrast CT.

OBJECTIVES: To develop and validate APEX-NET for early diagnosis and severity stratification of acute pancreatitis (AP) using non-contrast CT (NCCT), ...

Multi-omics approaches to parkinsonism: genomic, proteomic, and non-coding RNA perspectives.

Parkinson's disease (PD) is a progressive neurodegenerative disorder with significant variability associated with substantial loss of dopaminergic neu...

Artificial intelligence (AI)-assisted diagnosis of skin diseases: From image classification to dermatology-specific multimodal clinical reasoning.

Artificial intelligence (AI) in dermatology has moved beyond the early paradigm of single-image classification. Dermatological diagnosis is achieved b...

High angular resolution diffusion imaging of neurodevelopment in children through data creation with deep learning.

High-angular resolution diffusion imaging (HARDI) is an advanced method for characterizing brain microstructure and function. However, HARDI is time-c...

Artificial intelligence driven multiphysics analysis of Casson bioconvective ternary nanofluid flow over an inclined needle.

This study investigates the bio-convective flow of ternary Casson nanofluid across inclined moving thin needle embedded in a porous medium, considerin...

Tracer-agnostic diffusion model-based CT-free attenuation correction for brain PET: Comprehensive evaluation across 14 tracers.

OBJECTIVE: Accurate attenuation correction (AC) is critical in quantitative brain PET imaging. Conventional CT-based AC methods increase radiation exp...

Interpretable machine learning for Parkinson's disease diagnosis, staging, and biological mechanism exploration: a multicenter analysis.

OBJECTIVE: To develop and validate an interpretable machine learning model based on multicenter T1-weighted MRI radiomics data for the three-way class...

Integrating machine learning with histopathological, immunohistochemical, and PET parameters in the study of invasive breast carcinoma, no special type.

BACKGROUND: This study investigates the relationship between histopathological (HP) features, immunohistochemical (IHC) markers, 18F- FDG PET/CT param...

Predicting band gap from chemical composition: a comparative study of machine learning and deep learning models.

Predicting the band gap of inorganic semiconductors is crucial for designing materials used in electronic and optoelectronic applications. This study ...

JRadiEvo: A Japanese radiology report generation model enhanced by evolutionary optimization of model merging.

Radiology report generation is an important application of artificial intelligence (AI), as the interpretation of medical images and the production of...