Lymphoma

Clustering by patients-related characteristics identifies specific phenotypes with different prognosis after resection of non-small cell lung cancer: a French nationwide study from the Epithor database.

INTRODUCTION: Lung cancer remains the leading cause of cancer mortality worldwide despite advances in treatment. Patient-related factors beyond tumour characteristics may influence prognosis but are seldom integrated into staging or risk stratification. METHODS: We analysed data from 59 101 patients with resectable non-small cell lung cancer (NSCLC) in the French nationwide Epithor database. Using...

Interpretable multimodal PET/CT-EHR fusion via mixture-of-experts for prognostic stratification in mantle cell lymphoma: a multicenter study.

BACKGROUND: Mantle cell lymphoma (MCL) is a rare, biologically heterogeneous B-cell malignancy with highly variable outcomes. Existing prognostic tools are suboptimal. We developed an interpretable deep learning framework integrating baseline [18F]FDG PET/CT and electronic health record (EHR) data for individualized risk stratification. METHODS: In this multicenter study, 187 treatment-naïve MCL p...

Non-invasive diagnosis strategy integrating PSMA PET/CT and mpMRI for patients with suspected prostate cancer: a multi-center study.

BACKGROUND: Multiparametric MRI (mpMRI) and ^68 Ga-PSMA PET/CT are widely used for prostate cancer (PCa) diagnosis but remain limited by false positiv...

Diagnostic Accuracy of Ultrasound Radiomics for Cervical Lymph-Node Metastasis in Papillary Thyroid Carcinoma: Evidence Predominantly From Chinese Cohorts.

Pre-operative identification of cervical lymph-node metastasis (LNM) guides surgical extent in papillary thyroid carcinoma (PTC) but remains imperfect...

AI-guided discovery of the IRF4-PAICS-LDHA axis as a multitarget hub linking tumor metabolism to CD8+ T cell exhaustion in DLBCL.

Diffuse large B-cell lymphoma (DLBCL) features an immunosuppressive tumor microenvironment (TME), yet the molecular drivers connecting metabolic repro...

Deep learning inference of cell type-specific gene expression from breast tumor histopathology.

Cell type-specific gene expression from single-cell RNA sequencing (RNA-seq) is valuable for breast cancer precision oncology but available cohorts ar...

Integrated multi-omics analysis identifies TBC1D10C as an NK- and T cell-associated diagnostic biomarker in childhood obesity.

Childhood obesity is a growing global health crisis associated with an increased risk of metabolic and cardiovascular diseases in adulthood. While acc...

Development and validation of an MRI-based clinical-radiomics nomogram for predicting lymph node metastasis in non-small cell lung cancer.

A scale-down mini-bioreactor for the acceleration of data-driven bioprocess optimisation in cell therapy.

Cell therapies have demonstrated great potential for treating a broad range of diseases where conventional treatments have failed. However, long devel...

HP-DIL: Deep heterogeneity profiling with graph-informed disentangled interaction learning for MRI-based liver fibrosis staging.

Liver fibrosis staging (LFS) informs treatment decisions and prognostic assessment in liver disease. Multiparametric MRI enables non-invasive, quantit...

Augmenting Large Language Model With Prompt Engineering and Supervised Fine-Tuning in Non-Small Cell Lung Cancer Tumor-Node-Metastasis Staging: Framework Development and Validation.

BACKGROUND: Accurate tumor node metastasis (TNM) staging is fundamental for treatment planning and prognosis in non-small cell lung cancer (NSCLC). Ho...

Estimate renal cell carcinoma recurrence rates using electronic health records.

BACKGROUND: Lack of readily available recurrence data has limited the use of electronic health records (EHR) for risk assessment of cancer recurrence ...

Identifying demographic predictors of increased non-fatal opioid overdose risk among New York State Medicaid enrollees following the COVID-19 pandemic: an analysis of heterogeneous treatment effects.

BACKGROUND: Overdose rates in the U.S. rose dramatically during the COVID-19 pandemic. Well-documented racial and sociodemographic inequities in the i...

Exploration of the roles of SSR2 in hepatocellular carcinogenesis based on single-cell transcriptomics and spatial transcriptomics.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common types of cancer globally. However, HCC features poor prognosis due to complex pat...

Sharing a whole-/total-body [18F]FDG-PET/CT dataset with CT-derived segmentations: an ENHANCE.PET initiative.

We present a large whole-body and total-body curated dataset of dual-modality 2-deoxy-2-[18F]fluoro-D-glucose (FDG)-Positron Emission Tomography/Compu...

Clinicopathological and Imaging Distinction Between Ocular Adnexal MALT Lymphoma and IgG4-Related Ophthalmic Disease.

PURPOSE: To characterize clinicopathologic and imaging differences between ocular adnexal mucosa-associated lymphoid tissue lymphoma (OAML) and IgG4-r...

Enhanced precision in cell culture analytics: leveraging artificial intelligence for unbiased and non-destructive assessment of cell growth and viability.

Precise assessment of cell growth, count, and viability is a prerequisite for biological and medical research. Traditional cell analytics involve manu...

Pathology-Anchored Transcranial Sonography: A Cascaded Super-Resolution Deep Learning System for Early-Stage Parkinson's Disease Grading.

Delayed diagnosis of Parkinson's disease (PD) due to undetectable early pathological changes remains a major clinical challenge limiting effective tre...

PET-CT radiomics and artificial intelligence for predicting lymph node metastasis in cervical cancer: a systematic review and meta-analysis.

PURPOSE: Preoperative identification of lymph node metastasis (LNM) in cervical cancer is crucial for guiding therapeutic strategies but remains clini...

Non-invasive endometriosis staging prediction using integrated radiomics and spatiotemporal transformer model based on dynamic contrast-enhanced MRI.

Precise staging of endometriosis remains a clinical challenge, as current diagnosis depends almost entirely on laparoscopic visualization-an invasive ...