Other Cancers

Integrative advances in biomarker-driven prostate cancer management from genomic discovery to precision oncology.

Prostate cancer (PCa) is the second most common malignancy in men worldwide, with rising mortality linked to late-stage diagnoses. While current diagnostic strategies rely heavily on biomarker detection, their limitations highlight the need for comprehensive and integrative biomarker discovery. This review consolidates recent advances in PCa biomarkers, encompassing genetic, proteomic, liquid biop...

Evaluating the Performance of Artificial Intelligence in Accurately Detecting Skin Cancer: An Umbrella Review of Systematic Reviews and Meta-analyses.

BACKGROUND: Artificial intelligence technology is being widely developed in dermatology. However, there remains a lack of comprehensive data analyzing the diagnostic performance of artificial intelligence in skin cancer. OBJECTIVE: We aimed to evaluate the diagnostic accuracy of artificial intelligence in skin cancer detection. METHODS: MEDLINE, Embase, Cochrane library, Web of Science, and Scopus...

Endoscopy-based Deep Learning Algorithms versus Endoscopists in Early Esophageal Squamous Cell Carcinoma Detection: A Systematic Review and Meta-Analysis.

INTRODUCTION: To compare the diagnostic performance of endoscopy-based deep learning (DL) algorithms with endoscopists of different experience levels ...

Machine Learning-Based Survival Prediction Models for Young Patients With Gastric Cancer: Model Development and Validation Study.

BACKGROUND: Despite a global decline in the incidence of gastric cancer (GC), the number of cases diagnosed among younger individuals continues to inc...

[Emerging classifications of cardiometabolic risk in obesity].

Obesity, historically defined by body mass index and waist circumference, is a major risk factor for cardiometabolic complications; however, these ind...

Multicentre prospective cohort study to develop and validate a machine learning-based model for predicting 6-month all-cause mortality in elderly patients with advanced chronic obstructive pulmonary disease in China: study protocol.

INTRODUCTION: Chronic obstructive pulmonary disease (COPD) has an unpredictable clinical course, causing difficulties in short-term mortality predicti...

AI-driven multi-omics drug repurposing nominates AZD7762 as a multitarget inhibitor of IL22RA1 and FAM221A in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is an aggressive malignancy with limited targeted treatment options and poor clinical outcomes. We developed...

Automatic Localization and Classification of Crohn's Disease Activity in Computed Tomography Enterography Images Using Deep Learning.

Rapid and accurate localization and activity grading of Crohn's disease (CD) lesions on computed tomography enterography (CTE) images enhance the diag...

AI-based histopathology analysis predicts checkpoint inhibitor response in advanced melanoma and identifies patterns associated with response.

INTRODUCTION: Readily available predictive biomarkers for immune checkpoint inhibitor (ICI) response in advanced melanoma are limited. This study eval...

Machine learning-based preoperative classification of colorectal cancer stage using systemic inflammatory and nutritional biomarkers.

BACKGROUND: Accurate preoperative staging in colorectal cancer (CRC) is critical for determining the appropriate treatment strategy. This study evalua...

Leveraging the non-contrast CT component of PET/CT: an AI-driven delta-radiomics approach to monitor treatment response in metastatic breast cancer.

PURPOSE: 18 F-FDG PET/CT is the standard modality for monitoring treatment response in metastatic breast cancer. This study aims to evaluate the predi...

Risk Prediction of Early-Onset Hepatocellular Carcinoma: Derivation and Validation in a Nationwide Young Adult Cohort.

BACKGROUND: The global incidence of early-onset hepatocellular carcinoma (eHCC) is increasing significantly; however, specific risk prediction tools f...

Quantum Dot Encoding for In-Solution Single-Molecule Biomarker Counting in Metastatic Prostate Cancer.

Digital assays are in wide development for biomarker quantification at the single-molecule level, but the common use of surface pull-down steps limits...

Digital Pathology in Head and Neck Squamous Cell Carcinoma: Translational Advances and Clinical Integration for Pathologists, Oncologists, and Surgeons.

PURPOSE: Artificial intelligence (AI)-enabled digital pathology has advanced rapidly in head and neck squamous cell carcinoma (HNSCC), but its readine...

Integrative transcriptomic and single-cell analysis reveals metabolic reprogramming and hexosamine biosynthesis-mediated tumor microenvironment remodeling in prostate cancer.

BACKGROUND: Prostate cancer is one of the most common malignancies in men and exhibits substantial clinical heterogeneity. A considerable proportion o...

A review of deep learning-based multimodal data integration of lung cancer.

This is a narrative review that provides a perspective on the recent advances in deep learning (DL)-driven multimodal data integration for lung cancer...

Prediction and Clinical Application of Central Lymph Node Metastasis in Papillary Thyroid Carcinoma Based on Multi-modal Ultrasound Feature Fusion: A Multi-center Study.

OBJECTIVE: To develop and validate a deep learning model integrating multi-modal ultrasound information from B-mode ultrasound (BMUS) and strain elast...

Progression-guided spatiotemporal memory transformers for accurate and consistent longitudinal brain tumor segmentation.

For monitoring the progression of the disease and the efficacy of treatment, it is essential to segment the brain tumor. The majority of the available...

In silico discovery of novel small-molecule PD-L1 inhibitors through a multi-stage computational workflow integrating machine learning and molecular dynamics.

Cancer immunotherapy targeting the PD-1/PD-L1 pathway has transformed modern oncology; however, developing small-molecule inhibitors as viable alterna...

Artificial intelligence in cancer diagnosis and therapy using sex and gender as precision biomarkers.

Sex and gender represent critical yet underutilized precision biomarkers in oncology, influencing cancer incidence, progression, treatment response, a...