Other Cancers

Label-Free Prediction of EGFR Mutation Status Using Fluorescence Lifetime Imaging and Deep Learning in Lung Adenocarcinoma.

UNLABELLED: Accurate prediction of epidermal growth factor receptor (EGFR) mutations is essential for guiding targeted therapy in non-small cell lung cancer (NSCLC) and is routinely performed in clinical pathology samples. Current diagnostic practices rely on molecular techniques such as PCR-based assays and next-generation sequencing, which are often costly, time-consuming, and destructive to tis...

Machine learning modeling to predict HCC locations in cirrhotic patients undergoing MRI - a proof-of-concept study.

PURPOSE: Current hepatocellular carcinoma (HCC) surveillance guidelines rely on manually defined LI-RADS (Liver Imaging Reporting and Data System) features rather than imaging data analysis. This study evaluates the feasibility of machine-learning (ML)-based image analysis frameworks to identify and localize hepatic parenchyma at elevated risk for HCC. METHODS: In this retrospective study, cirrhot...

A machine learning-guided epithelial plasticity score refines prognostication and immune-context stratification in muscle-invasive bladder cancer.

PURPOSE: Muscle-invasive bladder cancer (MIBC) remains biologically heterogeneous, and clinicopathological variables do not fully capture epithelial-s...

Examining explainable artificial intelligence in TNM staging with PET-CT: a user-centred observation study.

PURPOSE: Artificial intelligence (AI) is increasingly proposed as a solution to improve efficiency in radiology and nuclear medicine, particularly in ...

Pharmacogenomics in oncology: mutation-targeted therapy and biomarker integration in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is the most common cancer-related cause of death among all countries globally, mostly because of late diagnosis, he...

Disease-modifying antirheumatic drugs (DMARDs) for rheumatoid arthritis after failure of biologic or targeted synthetic therapy: a systematic review and network meta-analysis.

RATIONALE: After inadequate response to first-line biologic or targeted synthetic (b/ts) disease-modifying antirheumatic drug (DMARD) therapy in adult...

Activated Cancer-Associated Fibroblasts Are Associated with Immunosuppression and Poor Prognosis in Clear Cell Renal Cell Carcinoma.

INTRODUCTION: Clear cell renal cell carcinoma (ccRCC) exhibits substantial heterogeneity within its tumor microenvironment, contributing to variable c...

Toward a Better Paradigm for Head and Neck Cancer Treatment Applying AI (HNC-TACTIC): Protocol for an International Cohort Study of Electronic Health Records.

BACKGROUND: Head and neck squamous cell carcinomas (HNSCCs) cause considerable morbidity and mortality. Multimodal treatment strategies can cause sign...

An advanced AI-driven deep learning framework for early detection and precise diagnosis of breast cancer from medical images.

A malignant disorder known as breast cancer (BC) arises when cells in breast tissue grow out of control, frequently due to genetic, hormonal, or envir...

Bidirectional microbiota-cancer crosstalk: Emerging platforms for advanced diagnostics and precision therapeutics in oncology.

Cancer is among the major causes of morbidity and mortality worldwide, and current treatment methods are limited by various drawbacks such as drug res...

Serum metabolomics profiling in head and neck squamous cell carcinoma: a multicentre diagnostic study.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is frequently diagnosed at advanced stages, when outcomes are poor. Biomarkers for HNSCC det...

Artificial intelligence for comprehensive skeletal maturity assessment: a unified CBCT-based deep learning framework.

Skeletal maturity assessment is crucial, and the cervical vertebral maturity (CVM), spheno-occipital synchondrosis (SOS), and mid-palatal suture (MPS)...

Deep learning-based CD8+ T cell model for predicting prognosis and‌ targeted immunotherapy benefit in ccRCC.

Deep learning holds significant promise for improving clear cell renal cell carcinoma (ccRCC) diagnosis and treatment. However, studies concerning tum...

Machine learning-based prediction of overall survival in non-metastatic renal cell carcinoma after radical nephrectomy.

Prognostic heterogeneity remains a challenge for non-metastatic renal cell carcinoma (RCC) patients following radical nephrectomy (RN). This study aim...

A Multimodal, Multitask Prediction Framework for Diagnosis and Prognosis of Clear Cell Renal Cell Carcinoma.

The purpose of this study is to develop and validate a multimodal, multitask prediction framework for clear cell renal cell carcinoma (ccRCC) by integ...

Pilot Study on Contrast-Enhanced CT-Based 3D Cascaded Segmentation of Hypopharyngeal Cancer and the Stability of the Extracted Radiomics Features.

Hypopharyngeal cancer (HPC), a malignant head and neck tumor with poor prognosis, requires accurate pretreatment segmentation for surgical planning an...

Deep learning single-cell analysis for cytologic evaluation of oral potentially malignant disorders.

Oral potentially malignant disorders (OPMDs) such as leukoplakia and erythroplakia may harbor dysplasia or progress to oral squamous cell carcinoma (O...

Intratumoral distribution of anisokaryosis in canine cutaneous mast cell tumors.

Automated measurements of anisokaryosis in canine cutaneous mast cell tumors (ccMCTs) have been shown to be predictive of survival, but questions rema...

Integrated bulk and single-cell transcriptomic analysis reveals the impact of lactate-related genes on prognosis and immune characteristics in HNSCC.

Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous malignancy with poor prognosis, accompanied by metabolic reprogramming and tum...

Machine learning and multi-omic empowered risk stratification and therapeutic framework targeting nucleotide metabolism and mast cell for stomach adenocarcinoma patients.

BACKGROUND: Mast cell and nucleotide metabolism(NM) encodes the Stomach adenocarcinoma (STAD) progression and tumor immune microenvironment(TME) heter...