Other Cancers

Geometric-aware deep learning for deciphering tissue structure from spatially resolved transcriptomics.

Recent advances in spatially resolved transcriptomics have enabled large-scale measurement of gene expression while preserving spatial context, facilitating the investigation of spatial heterogeneity within tissues. In this study, we propose SpatialGEO, a geometric-aware deep learning framework that integrates gene expression profiles with spatial coordinates to generate biologically meaningful lo...

Integrative single-cell and spatial transcriptomic analysis reveals a lactate-driven crosstalk between NFATc4⁺ tumor cells and SPP1⁺ macrophages in glioblastoma.

BACKGROUND: Glioblastoma (GBM) remains a lethal brain tumor with limited therapeutic options. Metabolic reprogramming, particularly lactate metabolism, plays a critical role in tumor progression and immune evasion. METHODS: Here, we integrated single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and machine learning to investigate the heterogeneity of lactate metabolism in GBM. RESULTS...

Deep learning-based malignancy probability estimation of pulmonary nodules in PET/CT imaging.

OBJECTIVE: The current BTS guidelines recommend evaluation of suspicious pulmonary nodules using [18F]FDG-PET/CT imaging, followed by Herder model ris...

Mapping oral-systemic health relationships: a data-driven analysis of co-occurrence patterns in biomedical literature.

OBJECTIVE: To systematically map co-occurrence patterns between systemic medical conditions and oral diseases in the biomedical literature. MATERIALS ...

Periodic surveillance of intraductal papillary mucinous neoplasms: gaps in evidence and future directions.

Intraductal papillary mucinous neoplasm (IPMN) is a well-established precursor to pancreatic cancer; however, its generally indolent biological behavi...

Comparison of radiomics handcrafted features and deep features in 18F-FDG PET/CT for differentiating benign and malignant persistent pulmonary ground-glass nodules.

BACKGROUND: The differentiation between benign and malignant persistent pulmonary ground-glass nodules (GGNs) remains challenging, and the relative va...

Glycosylation Signatures of Thyroglobulin in Papillary Thyroid Carcinoma.

Thyroglobulin (Tg) is a clinically established biomarker for thyroid cancer; however, its diagnostic specificity remains limited due to confounding be...

Combining pathology artificial intelligence and genomic biomarkers to refine long-term postprostatectomy outcome prediction.

BACKGROUND: A multimodal AI (MMAI) model has been validated in prostate biopsy specimens to guide treatment intensification in men receiving radiation...

Machine learning prediction of local control after Gamma Knife radiosurgery to post-resection cavities from brain metastases: a proof-of-concept study.

BACKGROUND: Large symptomatic brain metastases require initial surgical resection. However, local control (LC) after Gamma Knife radiosurgery (GKRS) t...

A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing.

Cell-free DNA (cfDNA) in body fluids enables noninvasive cancer detection. Multifeature artificial intelligence (AI) can improve sensitivity by integr...

Pulmonary nodule prediction in the multi-omics era: integrating radiomics, AI, liquid biopsy, and airway classifiers.

Low-dose CT (LDCT) lung cancer screening significantly reduces mortality but has dramatically increased the detection of pulmonary nodules. Most of th...

A Multimodal Multitask Deep Learning Model Based on Ultrasound RF Signals for Joint Assessment of Breast Masses and Axillary Lymph Nodes Status.

PURPOSE: Developing a deep learning model to simultaneously evaluate lymph node status and distinguish between benign and malignant breast masses has ...

Identification of therapeutic targets and postoperative recurrence prediction model construction for hepatocellular carcinoma based on systematic mendelian randomization.

BACKGROUND AND STUDY AIMS: Hepatocellular carcinoma (HCC) has a high risk of postoperative recurrence. This study aimed to develop a transcriptome-bas...

Prediction of microvascular invasion in hepatocellular carcinoma using contrast-enhanced ultrasound and deep learning.

Microvascular invasion (MVI) is a key prognostic factor in hepatocellular carcinoma but is currently only detectable after surgery. Here, we develop M...

A Whole-Body PSMA-PET/CT dataset with manually annotated tumor lesions.

We describe a publicly available, large, annotated dataset of 597 whole-body Positron Emission Tomography/Computed Tomography (PET/CT) studies with Pr...

Enhancing tumor T cell antigen prediction by integrating deep protein representations.

BACKGROUND: Cancer is a major threat to human health, and cancer immunotherapy is considered the most promising treatment option. It offers high effec...

Uncovering the mechanism of DCLK3 in colorectal cancer progression through WGCNA and machine learning.

BACKGROUND: Colorectal cancer (CRC) is a prevalent malignant tumor of the digestive tract with high morbidity and mortality rates. Although doublecort...

A machine learning-driven multitask framework for antibiotic resistance prediction in Escherichia coli, Klebsiella pneumoniae, and Enterobacter cloacae bloodstream infections among hematological malignancy patients.

BACKGROUND: Inappropriate empirical antimicrobial therapy (IEAT) significantly increases mortality in patients with resistant Gram-negative bacteremia...

AI-Based Analysis of Tumor-Infiltrating Lymphocytes and Homologous Recombination in Ovarian Cancer: JGOG3025-A1 Study.

Understanding the tumor immune microenvironment, especially tumor-infiltrating lymphocytes (TILs), remains crucial in ovarian cancer. However, the dis...

Brain network correlates of fatigue, depression, and anxiety in patients with Crohn's Disease in different disease states.

BACKGROUND: Symptoms of fatigue, depression or anxiety are frequent in Crohn's Disease (CD) and may relate to disturbed brain-gut interactions. While ...