Lymphoma

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 positives and modest specificity, particularly in distinguishing benign prostate diseases (BPDs) and clinically significant PCa (csPCa). Existing studies often rely on small, single-center cohorts with limited generalizability. This study aimed to develop a...

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...

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 ...

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 measure...

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 subje...