Hematology

Lymphoma

Latest AI and machine learning research in lymphoma for healthcare professionals.

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Estimation of the chemical-induced eye injury using a weight-of-evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part I: irritation potential.

Evaluation of potential chemical-induced eye injury through irritation and corrosion is required to ensure occupational and consumer safety for industrial, household and cosmetic ingredient chemicals. The historical method for evaluating eye irritant and corrosion potential of chemicals is the rabbit Draize test. However, the Draize test is controversial and its use is diminishing - the EU 7th Ame...

Dec 8 2014 25497990

Latent feature representation with stacked auto-encoder for AD/MCI diagnosis.

Recently, there have been great interests for computer-aided diagnosis of Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairment (MCI). Unlike the previous methods that considered simple low-level features such as gray matter tissue volumes from MRI, and mean signal intensities from PET, in this paper, we propose a deep learning-based latent feature representation with a stack...

Dec 22 2013 24363140
Novel Entropy-Based Framework for Quantifying Dynamic Epistemic Uncertainty in Clinical Medicine

The widespread adoption of clinical large language models (LLMs) introduces significant risks of automation bias, premature closure, and clinician des...

CCIDeconv: Hierarchical model for deconvolution of subcellular cell-cell interactions in single-cell data

Cell-cell interaction (CCI) underlies several fundamental biological processes, including development, homeostasis and disease progression. Subcellula...

SAGE: Stability-Aware Graph-Based Ensemble Feature Selection for Explainable Postpartum Depression Risk Prediction

Postpartum depression (PPD) poses a major burden on maternal and child health, especially in low- and middle-income countries where prevalence exceeds...

Aug 24 2026 2608.22809v1
Spending Scarce Confirmatory PET Measurements: Target-Aligned Validation in A4/LEARN

Anti-amyloid therapies and blood-based biomarkers are changing Alzheimer disease workups into a two-stage measurement workflow: screen broadly with ch...

Aug 23 2026 2608.22223v1
AsymFeX: A Symmetry-Driven Framework for Ischemic Stroke Segmentation Across Imaging Modalities and Stroke Stages

Fast and accurate segmentation of Acute Ischemic Stroke (AIS) lesions is essential for stroke prognosis and treatment planning. Non-contrast CT (NCCT)...

Aug 20 2026 2608.19769v1
When Two Tracers Disagree: An Investigation of Multimodal Fusion for Clinical PET/CT Segmentation

PSMA and FDG PET/CT visualise complementary biological information in prostate cancer. Combining both tracers could capture heterogeneous tumour pheno...

Aug 19 2026 2608.19063v1
Harnessing Magnitude-Only and Complex Measurements for Improved Dynamic MRI Reconstruction with Learned Priors

MRI reconstruction methods for undersampled k-space data naturally utilize complex-valued measurements. Parallel developments in sparse phase retrieva...

Aug 18 2026 2608.18036v1
FluoroFate: A generalisable platform for time-resolved single-cell analysis of cell fate enables quantification of cell death dynamics

Fundamental cellular decisions of life and death are governed by intricate and tightly regulated intracellular signalling pathways that determine whet...

Machine learning models for predicting prostate cancer and clinically significant prostate cancer at biopsy: An updated analysis of an expanded Japanese cohort

BackgroundA 2019 report from our institution described a multilayer artificial neural network (ANN) for predicting prostate cancer at biopsy in 334 pa...

Harnessing Pathology Foundation Models to Accelerate Lymphoma Diagnosis Through Automated Immunohistochemistry Triage

Pathologic diagnoses of hematopoietic diseases require immunohistochemistry (IHC) stains selected by pathologists upon preview of H&E-stained slides. ...

PET/CT Radiogenomic Mutation Prediction in Non-Small Cell Lung Cancer Using Multi-Label Learning

Lung cancer remains one of the leading causes of cancer- related mortality worldwide. Although targeted therapies have improved outcomes for patients ...

Aug 10 2026 2608.09721v1
Resolution Meets Reduction: Efficient Visual Context for 3D Radiology Report Generation

Vision-language models offer a promising path toward automating radiology report generation, but applying them to full 3D CT volumes poses substantial...

Aug 9 2026 2608.08713v1
PGViS: Personal Genome Variant interpretation Score for lung cancer genomes

Inherited lung cancer risk arises from both protein-coding and non-coding germline variants, but the functional non-coding component is largely unchar...

MirrorNet: Can Medical Image Anonymization Really Protect Patient Identity?

Medical images are routinely de-identified---names, dates, and other metadata removed---and then shared for research, teaching, and public benchmarks ...

Aug 6 2026 2608.05938v1
Dual-domain U-Nets with embedded back projection operators for motion-resolved 4D CBCT reconstruction

Four-dimensional cone beam CT (4D CBCT) is important for image-guided radiation therapy of thoracic cancers, but its use is limited by long scan times...

Aug 4 2026 2608.03430v1
Pixel Ignores, Superpixel Sees: Adverse Weather Image Restoration via Semantic-Center SSM

Adverse weather image restoration aims to recover clear visibility from degraded images in complex weather conditions. Existing works attempt to add...

Aug 3 2026 2608.01760v1
TELLER: Non-intrusive Cross-Layer Root-Cause Analysis for LLM Inference

Large language model (LLM) inference has evolved from an offline workload into a continuously operated software service, yet root-cause analysis remai...

Aug 3 2026 2608.01975v1
GIFT: Geometry-Invariant Fine-Tuning for Non-Lambertian Monocular Depth Estimation

Monocular depth foundation models, benefiting from large-scale synthetic training data, have demonstrated strong generalization. However, they often h...

Aug 3 2026 2608.02068v1
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