Lymphoma

Simulation-based inference captures non-Markovian effects as exemplified in protein production kinetics through cell division.

Inferring protein production kinetics in dividing cells is complicated by protein inheritance from the mother cell. For instance, fluorescence measurements commonly used to assess gene activation may reflect not only newly produced proteins but also those inherited through successive cell divisions. In such cases, observed protein levels in any given cell are shaped by its division history. As a c...

FetalSleepNet: A Transfer Learning Framework with Spectral Equalisation Domain Adaptation for Fetal Sleep State Classification.

OBJECTIVE: Fetal sleep state classification is essential for identifying neurodevelopmental complications like hypoxia, but manual annotation is subjective and labor intensive, and fetal EEG (fEEG) data is extremely scarce. METHODS: We propose FetalSleepNet, the first deep learning architecture specifically developed for automated sleep staging from the fEEG. To address the scarcity of labeled dat...

Imaging-based stratification of Claudin 18.2-positive gastric adenocarcinoma using 18F-FDG PET/CT radiomics.

PURPOSE: This study aimed to develop and validate a non-invasive, multimodal radiomics model based on preoperative 1⁸F-FDG PET/CT to predict CLDN18.2 ...

Organ-Aware Cross-Modality Registration Enables Attenuation Correction Without Repeated CT in Multi-Scan Total-Body PET/CT Imaging.

Multi-Scan Total-Body PET/CT imaging, including dual-time-point and multi-tracer protocols, provides valuable metabolic information for enhanced disea...

A fully automated CT-based pelvimetry pipeline for quantifying mid-pelvic surgical workspace in rectal cancer.

PURPOSE: Pelvimetry may aid preoperative planning in rectal cancer surgery, yet manual measurements are time-consuming and MRI-based methods require d...

Mapping intratumoral heterogeneity through PET-derived washout and deep learning after proton therapy.

The distribution of produced isotopes during proton therapy can be imaged with Positron Emission Tomography (PET) to verify dose delivery. However, bi...

Temporal AI-assisted compressed sensing for high-resolution, motion-robust small-bowel MR enterography without antiperistaltic agents: a feasibility study.

OBJECTIVES: To evaluate whether temporal AI-assisted compressed sensing (tACS) enables high-resolution, motion-robust magnetic resonance enterography ...

Predicting CO2 emissions and strength of FA-SF geopolymer mortar: An ANN approach for sustainable construction.

The construction industry is facing increasing pressure to reduce the CO2 emissions from conventional cement manufacturing. Geopolymer concrete, utili...

Evolution of the Diagnostic Paradigm for Giant Cell Arteritis: From Histopathology to Multi-Modal Imaging Integration Running title: GCA: Histology to Imaging.

Giant cell arteritis (GCA) is a systemic vasculitis that predominantly affects mediumand large-sized arteries. Delayed diagnosis may result in irrever...

CT data harmonization via learned virtual monoenergetic imaging for cross-kV scan translation and radiomics reproducibility.

BACKGROUND: Radiomics extracts quantitative imaging features from computed tomography (CT) data for clinical decision-making. However, variations in a...

Interpretable LightGBM model with SHAP analysis predicts non-excellent response to initial radioiodine therapy in differentiated thyroid carcinoma.

PURPOSE: To identify independent determinants influencing therapeutic outcomes of initial radioactive iodine (1 3 1I) therapy in differentiated thyroi...

A metabolite-augmented FIB-4 machine learning panel achieves superior liver fibrosis staging in chronic liver disease.

Accurate, non-invasive liver fibrosis detection is essential for chronic liver disease management, particularly with rising metabolic dysfunction-asso...

Short-chain fatty acid-producing microbes differentiate non-infectious and infectious neutropenic fever in leukemia.

UNLABELLED: Neutropenic fever (NF) is often the first sign of infection in patients with hematologic malignancies, but its cause is frequently unknown...

AI-assessed sarcopenia as an independent predictor of neoadjuvant chemotherapy outcomes in muscle-invasive bladder cancer.

PURPOSE: Sarcopenia has already been widely investigated as a potential indicator of negative outcomes in oncology patients. Our aim was to evaluate t...

Synchronization of state-dependent switched neural networks via non-exponential lyapunov functions with stochastic delayed impulses.

This paper studies the synchronization of switched neural networks (SNNs) under stochastic delayed impulses (SDI), utilizing the state-dependent switc...

Artificial Intelligence in Periodontology: A Systematic Review.

AIM: To provide a comprehensive review of artificial intelligence (AI) applications in periodontology, focusing (1) on deep learning for image-based d...

Comparative evaluation of magnetic metal oxide nanoparticles for microorganism concentration: From standard strains to cerebrospinal fluid samples using statistical and artificial neural network modeling.

Magnetic nanoparticle based concentration of microorganisms is an effective strategy for improving detection efficiency in low biomass biological samp...

Detection of defective cocoa beans using machine learning techniques and NIR spectral data fusion.

Cocoa beans are graded according to the degree of fermentation and the presence of defects, which are typically assessed using conventional cut tests....

Personalized mapping of body homeostasis using whole-body PET connectomics and routine FDG PET imaging.

BACKGROUND: Immuno-inflammation and systemic alterations are key features of chronic diseases. While PET molecular imaging is widely used in precision...

The Effect of Parrot Therapy on During Venipuncture Pain in Chronic Patients.

OBJECTIVE: There are no randomized controlled trial (RCT) in the current literature comparing live, robotic, and visual animal-based therapies. This s...