Lymphoma

CT-less TOF PET: challenges and innovations for quantitative imaging.

A decade has passed since the groundbreaking work by Defrise et al. (2012), which demonstrated that TOF PET imaging is self-correcting for a variety of physical degradation factors, most notably attenuation correction, which is currently based on CT imaging in PET-CT scans. At that time, the acronym for Maximum-Likelihood reconstruction of Attenuation and Activity, MLAA, became widely used in appl...

Deep learning-based CT radiomics for ALK rearrangement status prediction in lung adenocarcinoma.

BACKGROUND: Current clinical guidelines mandate routine evaluation of anaplastic lymphoma kinase (ALK) rearrangement in lung adenocarcinoma prior to ALK-targeted therapy initiation. This study aimed to develop and validate a non-invasive predictive model integrating deep learning radiomic (DLR) features from pre-treatment computed tomography (CT) images with clinical data to improve pretherapeutic...

Metaheuristic optimization of deep CNNs for multi-class diagnosis of cervical cancer and lymphoma.

Accurate and early diagnosis of cancer is critical for determining effective treatment strategies and improving patient survival rates. However, autom...

Convolutional neural network analysis of cervical CT images: classification of Kikuchi disease, lymphoma, lymphadenitis, and tuberculosis.

BACKGROUND: Kikuchi disease, lymphoma, lymphadenitis, and tuberculosis are common diseases affecting the head and neck. The causes and treatment metho...

Pregnancy prediction in Nelore heifers using machine learning algorithms.

Beef cattle production systems, particularly those based on Nelore heifers in tropical regions, are under increasing pressure to improve reproductive ...

Comparative classification of spectrally overlapping Allium seed genotypes using Vis-NIR spectroscopy and hyperspectral imaging with chemometric, machine, and deep learning models.

Accurate identification of Allium seed genotypes is essential for cultivar authentication, breeding, and fraud prevention, yet remains challenging due...

Crowdsourcing enables robust cell annotation for breast cancer pathology.

The tumor microenvironment (TME) contains important morphological and molecular cues that help determine prognosis and therapeutic responses. Deep lea...

Four Directions, One Solution: Enabling Rapid Diffusion Tensor MRI for Ultra-Low Field Using Deep Learning.

PURPOSE: This study revisits the tetrahedral encoding strategy originally proposed to accelerate Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) ...

Near-infrared imaging-based high-content analysis for label-free assessment of internal cellular heterogeneity in spheroid.

Non-invasive analysis of spheroid quality was essential because spheroids better recapitulated in vivo-like cell-cell and cell-extracellular matrix (E...

Precision theranostics in oncology: integrating antibody-drug conjugates, radioimmunotherapy, and immuno‑PET for adaptive cancer care.

The century-old vision of a "magic bullet" in oncology is being realized through the paradigm of precision theranostics, which formally integrates tar...

Flux sampling and graph neural networks for improved gene essentiality prediction in mammalian genome-scale metabolic models.

Gene essentiality, the requirement of a gene for survival or proliferation, is central to understanding cellular processes and identifying drug target...

Consistency analysis of AI cell recognition results between non anticoagulant and anticoagulant marrow smear after Wright's staining.

The integration of artificial intelligence with bone marrow cytology represents a significant trend in the application of AI image recognition technol...

The geographic digital divide among dementia caregivers in the U.S.: a cross-sectional study.

BACKGROUND: Digital health tools, particularly patient portals, can support caregiving, but there is limited understanding of how sociodemographic and...

Top five Alzheimer Disease trial eligibility criteria favor men compared to women in a clinic-based cohort.

BACKGROUND: Less women participate in Alzheimer Disease (AD) trials compared to their estimated representation in the global dementia population. OBJE...

Deep learning model for noninvasive prediction of Ki-67 expression and prognostic stratification in breast cancer: a multicenter retrospective study.

OBJECTIVE: Ki-67 correlates with prognosis for patients with breast cancer. However, the evaluation of Ki-67expression relies on pathological analysis...

Intelligent optimization of micro-electrical discharge machining of aluminum nitride ceramics using nano abrasive zirconium oxide-enhanced biodegradable dielectric.

This study explores the use of nano-enhanced Canola Oil Methyl Ester (COME) formulated with 0.5 wt% of zirconium oxide (ZrO2) nanoparticles as a biode...

Design and in silico evaluation of an mRNA vaccine against HTLV-1 using AI-driven reverse vaccinology approaches.

Human T-lymphotropic virus type 1 (HTLV-1) is the first discovered human oncogenic retrovirus that can cause adult T-cell leukemia/lymphoma, HTLV-1-as...

CellFuse enables Multi-modal Integration of Single-cell and Spatial Proteomics Data for Systems-level Analysis in Cancer.

Analysis of tumors using single-cell and spatial modalities is critical to advance our understanding of cancer. The growth of technologies that enable...

Aerial LiDAR-Based, Source-Resolved Methane Emissions Inventory: Permian Basin Case Study for Benchmarking U.S. Emissions.

Reducing methane emissions can slow near-term warming, yet building accurate inventories to inform mitigation efforts and track progress toward reduct...

MRI Deep Learning for Differentiating Glioblastoma, IDH-Wildtype from Central Nervous System Diffuse Large B-cell Lymphoma.

Glioblastoma, IDH-wildtype (GBM) and central nervous system diffuse large B-Cell lymphoma (CNS-DLBCL) are aggressive brain tumors with overlapping MRI...