Other Cancers

Standardizing PSMA PET/CT reporting in prostate cancer: from structured frameworks to AI-assisted interpretation.

PSMA PET/CT is increasingly used for prostate cancer staging, restaging, treatment selection, and therapy response assessment. In parallel, several interpretation frameworks have been developed to standardize reporting. PROMISE version 2 integrates the PRIMARY score for local disease, molecular imaging TNM staging, and a PSMA expression score. PSMA-RADS 2.0 supports lesion-level characterization, ...

Automatic metabolic breast cancer staging using [¹⁸F]FDG PET/CT: comparison with nuclear medicine physician-based and clinical staging.

PURPOSE: This study aimed to evaluate a deep-learning (DL)-based framework to automatically perform breast cancer (BC) metabolic staging on [¹⁸F]FDG PET/CT, and to assess agreement among DL-based, nuclear medicine (NM) physician-based, and clinical staging. METHODS: A total of 403 histologically confirmed BC patients who underwent whole-body staging [¹⁸F]FDG PET/CT were retrospectively included. A...

Identification and validation of exosome-related biomarkers in pediatric glioblastoma.

Pediatric glioblastoma (pGBM) is an aggressive central nervous system (CNS) tumor whose pathological progression is significantly influenced by exosom...

Deep Learning in Dental Imaging: Advances, Challenges, and Future.

Artificial intelligence and deep learning have expanded dental imaging analysis by enabling automated detection, classification, localization, segment...

Combination of color-Doppler ultrasound and MRI to improve lacrimal gland lesion characterization: A machine learning approach.

PURPOSE: The purpose of this study was to develop a machine learning-based algorithm based on a combination of magnetic resonance imaging (MRI) and co...

Based on artificial intelligence-assisted generation and in-depth in-silico evaluation of potential inhibitors targeting Stearoyl-CoA desaturase 1 (SCD-1).

Stearoyl-CoA desaturase 1 (SCD-1), a key rate-limiting enzyme in lipid metabolism, catalyzes the conversion of saturated fatty acids to monounsaturate...

Benchmarking deep learning models for laryngeal cancer staging using the LaryngealCT dataset.

Laryngeal cancer imaging research lacks standardised public datasets to enable reproducible deep learning (DL) model development. We present Laryngeal...

Exploring the immune landscape and immunotherapy relevance of ER stress-related lncRNAs in melanoma through multi-omics and explainable machine learning.

BACKGROUND: Melanoma is a highly aggressive malignancy with poor clinical outcomes, and endoplasmic reticulum (ER) stress plays an important role in t...

Dissecting T-cell exhaustion heterogeneity and immune ecosystem dynamics in colorectal cancer through multi-omics machine learning.

BACKGROUND: Immunotherapy has shown limited efficacy in a substantial subset of CRC patients, yet the mechanisms underlying therapeutic resistance rem...

Body composition radiomics integrated with machine learning to predict prognosis in advanced NSCLC treated with first-line immunochemotherapy and concurrent radiotherapy.

OBJECTIVE: Adipose tissue is a highly heterogeneous and plastic endocrine and immune organ whose characteristics have been linked to prognosis in NSCL...

Machine learning-driven QSAR modeling combined with single cell transcriptomics identifies novel drug targets for lung cancer.

BACKGROUND: Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related mortality, largely due to frequent metastasis to the brain and bon...

Spatially interpretable artificial intelligence framework to tailored neoadjuvant dual HER2 blockade in HER2-positive breast cancer.

Neoadjuvant dual HER2 blockade with trastuzumab and pertuzumab plus chemotherapy represents the current standard-of-care for HER2-positive breast canc...

Differentiating sub-centimeter lung metastases in colorectal cancer by deep learning: a multicenter retrospective study.

BACKGROUND: Early diagnosis of sub-centimeter lung metastases is critical for timely decision-making and improved prognosis in patients with colorecta...

Risk stratification for reoperation outcomes in recurrent or persistent papillary thyroid carcinoma: development and validation of a machine learning model.

BACKGROUNDS: Reoperation is a key therapeutic strategy for recurrent or persistent papillary thyroid carcinoma (PTC), but its outcomes remain highly h...

Computational prediction of TCR cross-reactivity: principles, challenges and translational opportunities.

T-cell receptor (TCR) cross-reactivity, whereby a single TCR recognizes multiple peptide-MHC (pMHC) ligands, is essential for immune surveillance but ...

Development and Validation of a Machine Learning Model to Prognosticate Hepatocellular Carcinoma.

BACKGROUND: Prognostic models for hepatocellular carcinoma (HCC) may have limited accuracy. We aimed to construct and validate a novel prognostic mode...

Frontiers in Raman nano-diagnostics: SERS and TERS of extracellular vesicles for cancer detection.

Efforts to create rapid, non-invasive, and reliable cancer diagnostics have increasingly focused on extracellular vesicles (EVs), nanoscale carriers o...

Comparing clinical decision-making between colposcopists and large language models in cervical dysplasia management: a pilot prospective multicenter study.

PURPOSE: This prospective multicenter study aimed to compare the decision-making abilities of board-certified colposcopists and two commercially avail...

Location of AI risk markers and associated mammographic features in screening mammograms obtained years before screen-detected breast cancer.

OBJECTIVES: To examine screening mammograms assigned high-risk scores by two artificial intelligence (AI) models, 2 and 4 years prior to screen-detect...

Engineered small extracellular vesicles in hematologic malignancies: mechanisms, therapeutic strategies, and translational challenges.

Hematologic malignancies remain among the most challenging cancers to treat due to genetic heterogeneity, clonal evolution, and therapy resistance. Ex...