Colon Cancer

Evaluating Large Language Models for Colonoscopy Preparation Assistance: Correctness and Diversity in Synthetic Dialogues

Colorectal cancer is the third leading cause of cancer-related deaths in the United States, and colonoscopy remains the gold standard for early detection and prevention. However, many procedures are postponed due to inadequate bowel preparation, a preventable failure often caused by patients’ difficulty in understanding or following written prep instructions. Prior interventions such as reminder a...

IHGAMP: Pan-cancer HRD prediction from routine H&E whole-slide images using foundation models

Homologous recombination deficiency (HRD) confers sensitivity to poly (ADP-ribose) polymerase (PARP) inhibitors and platinum-based chemotherapy, representing a critical biomarker for precision oncology across multiple malignancies. Current HRD assessment relies on next-generation sequencing of genomic scar signatures, but specialized infrastructure requirements, high costs, and prolonged turnaroun...

Beyond Annotation: Leveraging Raw RNA-seq Reads via Foundation Models for Multi-Cancer Early Detection

Early cancer detection substantially improves patient survival, yet conventional screening methods are directed at single anatomical sites and inadequ...

ExCaPT: Explainable Cancer Prediction with Transformer-based models

Cancer remains one of the most significant global health challenges. De-spite advances in treatment, early detection remains a critical concern. The i...

Integrating Artificial Intelligence and Precision Medicine to Characterize JAK-STAT Pathway Alterations in FOLFOX-Treated Colorectal Cancer in Disproportionately Affected Groups

Early-onset colorectal cancer (EOCRC) continues to rise, with the steepest increases observed among Hispanic/Latino (H/L) populations, underscoring th...

Artificial Intelligence-Driven Precision Oncology Uncovers Prognostic Significance of RTK-RAS Alterations in FOLFOX-Treated Early-Onset Colorectal Cancer

The incidence of early-onset colorectal cancer (EOCRC; <50 years) is rising rapidly among populations. Although alterations in the RTK-RAS signaling p...

Machine Learning-Based Identification of Blood Biomarkers that Distinguish Precachectic and Cachectic Patients with Pancreatic Ductal Adenocarcinoma

Identification of minimally invasive biomarkers of different stages of cachexia (Ca), and precachexia (PCa) in particular, might help clinicians in tr...

Conversational Artificial Intelligence-Based Integration of Clinical and Genomic Data Identifies MAPK Alterations in Colorectal Cancer

Colorectal cancer (CRC) exhibits marked heterogeneity across age, ancestry, and treatment context, underscored by the rising incidence of early-onset ...

Early prediction of colorectal adenoma risk: leveraging large-language model for clinical electronic medical record data.

OBJECTIVE: To develop a non-invasive, radiation-free model for early colorectal adenoma prediction using clinical electronic medical record (EMR) data...

Tumor-infiltrating immune cell signature score reveals prognostic biomarkers and therapeutic targets for colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is one of the leading contributors to cancer-related deaths worldwide, with more than 900,000 new diagnoses and re...

TMEM132A: a novel susceptibility gene for lung adenocarcinoma combined with venous thromboembolism identified through comprehensive bioinformatic analysis.

BACKGROUND: Mounting evidence indicates that lung adenocarcinoma (LUAD) patients are at elevated risk for venous thromboembolism (VTE), presenting a m...

Use of artificial intelligence to measure colorectal polyp size without a reference object.

BACKGROUND AND STUDY AIMS: Polyp size is crucial for determining colonoscopy surveillance intervals. We present an artificial intelligence (AI) model ...

Diagnostic accuracy of artificial intelligence based on imaging data for predicting distant metastasis of colorectal cancer: a systematic review and meta-analysis.

BACKGROUND: Colorectal cancer is the third most common malignant tumor with the third highest incidence rate. Distant metastasis is the main cause of ...

Single-cell transcriptomics and machine learning unveil ferroptosis features in tumor-associated macrophages: Prognostic model and therapeutic strategies for lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is a major cause of cancer-related mortality worldwide. Tumor-associated macrophages (TAMs) play a crucial role...

Prediction of KRAS gene mutations in colorectal cancer using a CT-based radiomic model.

BACKGROUND: Determining the KRAS gene mutation status in colorectal cancer (CRC) before surgery is highly important for an individualized clinical tre...

Development of an immune-related gene signature applying Ridge method for improving immunotherapy responses and clinical outcomes in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is a major cause of cancer mortality. Considering the critical role of tumor infiltrating lymphocytes in effect...

Microbiota as diagnostic biomarkers: advancing early cancer detection and personalized therapeutic approaches through microbiome profiling.

The important function of microbiota as therapeutic modulators and diagnostic biomarkers in cancer has been shown by recent developments in microbiome...

Protocol for evaluating the cost-effectiveness of Mongolia's sugar-sweetened beverages tax using double machine learning.

Elevated consumption of sugar-sweetened beverages (SSBs) has been associated with an increase in obesity, type 2 diabetes, and other non-communicable ...

Identification of miR-20a as a Diagnostic and Prognostic Biomarker in Colorectal Cancer: MicroRNA Sequencing and Machine Learning Analysis.

INTRODUCTION: The differential expression of miRNAs, a key regulator in many cell signaling pathways, has been studied in various malignancies and may...

Artificial Intelligence Models Could Enhance the Diagnostic Accuracy (DA) of Fecal Immunochemical Test (FIT) in the Detection of Colorectal Adenoma in a Screening Setting.

BACKGROUND/AIM: This study evaluated the diagnostic accuracy (DA) for colorectal adenomas (CRA), screened by fecal immunochemical test (FIT), using fi...