Lymphoma

Beyond FDG: a paradigm shift in precision localization of epileptogenic zones in refractory epilepsy using multimodal molecular imaging (PET/CT) and isotropic 3D MRI fusion.

Surgical resection for drug-resistant focal epilepsy relies on the precise presurgical localization of the epileptogenic zone (EZ). Although [1⁸F]FDG-PET has historically served as a diagnostic cornerstone, its clinical utility is often constrained by anatomy-metabolism decoupling. This non-specific glucose hypometabolism frequently extends beyond the true EZ due to the bystander effect, complicat...

A deep learning model for speech-based prediction of clinical scores in people with Huntington's disease: a longitudinal study with cross-sectional replication.

BACKGROUND: Sensitive monitoring tools are needed to track progression in neurodegenerative diseases and assess interventions before overt brain damage occurs. We propose speech as a non-invasive, easily collected biomarker to capture disease-related variation over time. We developed and validated Neurodegenerative Disease Speech Network (NDSNet), an automated deep learning model that generates in...

Fast Submillimeter Whole-Brain T2*-Weighted Imaging Using 3D-EPI With CAIPIRINHA and Deep-Learning Denoising at 3T.

PURPOSE: Recent updates to the diagnostic criteria of multiple sclerosis (MS) require whole-brain T2*-weighted (T2*w) imaging with submillimeter resol...

Can machine learning uncover viable non-platinum catalysts for hydrogen evolution? An unsupervised clustering approach to transition metal-ligand complexes.

Hydrogen is central to the global clean energy transition, yet the widespread use of green hydrogen is constrained by its dependence on costly, supply...

Preoperative PET/CT phenotype of gastric-type endocervical adenocarcinoma: integrated morphological, metabolic, serological, and explainable machine-learning analysis.

PURPOSE: Gastric-type endocervical adenocarcinoma (GAS) is an aggressive, non-HPV-associated cervical adenocarcinoma that is often difficult to recogn...

Non-Invasive Triage of Bladder Outlet Obstruction and Detrusor Underactivity in Men With Lower Urinary Tract Symptoms: A Narrative Review and Conceptual Framework for Depth-Aware Multimodal Transcutaneous Testing.

INTRODUCTION: Differentiating bladder outlet obstruction (BOO) from detrusor underactivity (DU) remains a major unmet need in the management of lower ...

Automated deep learning detection of hepatic steatosis on non-contrast CT scans and discrepancy with scan reports.

BACKGROUND AND AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a major cause of liver disease that is growing in prevalence....

[Etiological investigation of inflammatory orbital disease in patients seen in internal medicine].

Inflammatory orbital diseases are characterized by inflammation that may involve any structure of the orbit including lacrimal gland, and may represen...

Predicting miRNA-disease associations based on adaptive neighborhood propagation and feature spatial recombination.

MicroRNAs (miRNAs) are critical regulators in biological processes such as cell proliferation, differentiation, and apoptosis, with their aberrant exp...

A combi-elasto ultrasound based deep learning model on liver fibrosis staging for suspected MASLD/MASH patients.

OBJECTIVES: Metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH) weakened the ...

Development and multicenter validation of an AI-driven detection system for DLBCL cells in bone marrow smears.

The presence of diffuse large B-cell lymphoma (DLBCL) cells in bone marrow (BM) smears is recognised as a key morphological basis for diagnosing BM in...

Incremental prognostic value of AI-based coronary CT angiography combined with PET/CT dynamic myocardial perfusion imaging in patients with suspected or confirmed coronary artery disease.

BACKGROUND: Coronary computed tomography angiography (CCTA) and positron emission tomography/computed tomography (PET/CT) myocardial perfusion imaging...

BASG-Net: a background-aware spatial gating network for cervical cell segmentation in pap smear images.

The precise segmentation of cervical cell images is regarded as a fundamental prerequisite for the implementation of computer-aided cervical cancer sc...

Prognostic survival models for diffuse large B-cell lymphoma using statistical and machine learning approaches.

Although diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease, existing prognostic tools, including the revised International Prognostic I...

Machine learning-guided discovery of withangulatin A as a novel inducer of megakaryocytic differentiation through direct targeting of TYK2 in leukemia.

BACKGROUND: Leukemia is an aggressive hematological malignancy. Effective differentiation-inducing agents for non-acute promyelocytic leukemia (non-AP...

Automated quantification of drug-induced cell death via vacuolation scoring in microscopic images.

Cell death plays a critical role in maintaining cellular homeostasis. The accurate evaluation of cell death is essential to determine the efficacy of ...

Masked attribution-based probing of strategies as a computational framework to align human, non-human primate, and model explanations.

What visual information do primate brains use to recognize objects, and can explanations from artificial neural networks (ANNs) help reveal these biol...

Evaluation of deep learning-based reconstruction models on non-TOF BGO PET/CT: impact of acquisition times and BSREM penalization factors on lesion detectability and SNR.

BACKGROUND: New long field-of-view (FOV) PET scanners using bismuth germanate (BGO) detectors without time-of-flight (TOF) capability are now availabl...

FUO-PETMamba: a pet maximum-intensity-projection-based artificial intelligence framework for aetiological classification of fever of unknown origin with multicentre validation.

BACKGROUND: Fever of unknown origin (FUO) remains diagnostically challenging because of heterogeneous causes, non-specific clinical manifestations, an...

A novel model of perceived sustainable work performance through the active bystander behavior, team cohesion, and innovative work behavior: A multi-analytical approach.

The study examines the relationships among active bystander behavior (ABSB), innovative work behavior (IWB), team cohesion (TC), and sustainable work ...