Lymphoma

Total monomeric anthocyanin concentration estimation of red wines based on color data using multivariate statistical analysis and machine learning.

BACKGROUND: Red wine is a high-value grape derivative containing complex chemical compounds that dictate its quality. Qualitative and quantitative determination of these compounds is essential for standardizing and classifying the product. This proof-of-concept study integrates chemometric methods and machine learning algorithms to establish predictive models for estimating total monomeric anthocy...

Filling the Gaps: Generating 4D Dense Cardiac Anatomy from Sparse CMR for Enhanced Tetralogy of Fallot Assessment.

BACKGROUND: Accurate assessment of 3D four chamber cardiac anatomy is essential for managing repaired Tetralogy of Fallot (rToF), yet standard cardiac magnetic resonance (CMR) protocols acquire sparse 2D slices with anisotropic resolution, inter-slice inconsistencies, and motion artifacts from patient movement and incomplete acquisitions. As CT provides isotropic 3D whole-heart segmentations, it c...

Investigating AD and non-AD [18F]flortaucipir distribution patterns in a memory clinic cohort.

PURPOSE: Amyloid (A) deposition represents a specific pathological hallmark of Alzheimer's disease (AD). Clinical diagnostic protocols frequently rely...

A radio-pathological fusion model for predicting PD-L1 expression and immunotherapy response in non-small cell lung cancer.

OBJECTIVE: This study aims to construct a multimodal fusion model (FM) based on CT and hematoxylin and eosin (H&E) stained slices to predict the PD-L1...

Multimodal multitask deep learning for grading management system in non-small cell lung cancer.

Accurate histologic subtyping, tumor node metastasis classification (TNM) staging and prognostic assessment are central to clinical management of non-...

Non-invasive imaging diagnostic techniques in metabolic dysfunction-associated steatotic liver disease: a roadmap for clinicians.

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously termed nonalcoholic fatty liver disease (NAFLD), is the most prevalent ch...

Comparative machinability and neural network-driven optimization of AISI D2 steel using chamfered and conventional tooling.

Dry turning of AISI D2 steel requires a balance between productivity, surface integrity, thermal loading, and energy demand. This study compares the m...

Development of a prediction model for infectious mononucleosis using machine learning algorithms based on blood cell analysis parameters.

BACKGROUND: Infectious mononucleosis (IM) presents with nonspecific clinical manifestations, leading to frequent misdiagnosis or delayed diagnosis, an...

DVNDTA: a dual virtual node based heterogeneous interaction model for accurate prediction of drug-target affinity.

Efficient prediction of drug-target affinity (DTA) is crucial for accelerating drug discovery. Recently, deep learning approaches leveraging 3D comple...

Comprehensive framework for evaluation of deep neural networks in detection and quantification of lymphoma from PET/CT images: Clinical insights, pitfalls, and observer agreement analyses.

PURPOSE: This study addresses critical gaps in automated lymphoma segmentation from PET/CT imaging, often overlooked in prior work. While deep learnin...

New Frontiers of Skin Ultrasound in Precision Medicine.

Ultrasound has emerged as a versatile, non-invasive imaging technique in dermatology, offering real-time, high-resolution visualization of cutaneous s...

Adaptive kNN graph model.

The k-nearest neighbors (kNN) algorithm is a cornerstone of non-parametric classification in artificial intelligence, yet its deployment in large-scal...

Performance of GPT-based large language models in hepatocellular carcinoma stratification: liver function assessment, BCLC staging, and treatment recommendations.

Large language models (LLMs) like GPT have been proposed to support complex clinical decision-making. This study evaluated the performance of GPT-base...

Interpretable machine learning distinguishes skip from continuous metastasis in N1b papillary thyroid carcinoma.

Skip metastasis-defined as lateral lymph node metastasis(N1b) in the absence of central lymph node involvement-represents a distinct yet underrecogniz...

An artificial intelligence model to detect abnormal ejection fraction from non-contrast chest computed tomography: the CT-LVEF study.

AIMS: Heart failure (HF), a major global health challenge, affects millions worldwide and poses substantial healthcare and economic burdens. It is est...

Spinal cord FDG PET uptake in healthy adults: an AI-driven segmentation study.

PURPOSE: 18F-fluorodeoxyglucose (FDG) Positron Emission Tomography (PET)/Computerized Tomography (CT) is an important imaging modality in oncology, bu...

Multimodal assessment of minimally conscious state and cognitive motor dissociation in neurocritical care: A critical review.

Minimally conscious state (MCS) is characterized by inconsistent but clearly discernible clinical and behavioral evidence of consciousness. Cognitive ...

Computational pathology model to predict recurrence-free survival in NMPUC patients on BCG-therapy.

Urothelial carcinoma, predominantly appearing as non-muscle-invasive papillary urothelial carcinoma (NMIPUC), exhibits wide clinical variability. Accu...

Analysis of vehicle-related non-exhaust PM10 and emerging pollutants in Beijing with machine-learning.

With the growth of electric vehicles, non-exhaust PM10 is becoming the dominant contributor to vehicle-related particulate pollution and a source of e...

Hierarchical semantic extraction and heterogeneous graph neural networks for event-driven time series forecasting.

Event-driven time series forecasting constitutes a fundamental challenge across multiple scientific domains. Existing deep learning approaches rely on...