AIMC Topic: Esophageal Neoplasms

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A machine-learning informed circulating microbial DNA signature for early diagnosis of esophageal adenocarcinoma.

Gut microbes
Esophageal adenocarcinoma (EAC) has seen a dramatic rise in incidence in developed countries over the past three decades. Early detection of its precursors-gastroesophageal reflux disease (GERD), Barrett's esophagus (BE), and high-grade dysplasia (HG...

Development and validation of an interpretable Random Forest model for predicting recurrence after endoscopic submucosal dissection in superficial oesophageal squamous cell carcinoma.

Annals of medicine
BACKGROUND: Currently, endoscopic submucosal dissection (ESD) has become the preferred treatment for superficial oesophageal squamous cell carcinoma (SESCC). However, due to the residual background mucosa, some patients are still at risk of postopera...

Interpretable multimodal radiopathomics model predicting pathological complete response to neoadjuvant chemoimmunotherapy in esophageal squamous cell carcinoma.

Journal for immunotherapy of cancer
BACKGROUND: Accurate preoperative prediction of pathological complete response (pCR) following neoadjuvant chemoimmunotherapy (nCIT) could help individualize treatment for patients with esophageal squamous cell carcinoma (ESCC). This study aimed to d...

Cell-free DNA methylation and fragmentomics-based liquid biopsy for accurate esophageal cancer detection.

BMC cancer
BACKGROUND: Cell-free DNA is a promising source of biomarkers for early cancer detection and carries tumor-driven methylation and fragmentation features that have achieved good diagnostic efficacy across various cancers. However, there were no studie...

Predictive modeling of flavonoid efficacy against esophageal carcinoma: a comprehensive approach.

Scientific reports
Esophageal carcinoma poses a significant health challenge, particularly due to its notably high prevalence in East Asia, which underscores the urgent need for innovative treatment strategies. Natural flavonoids are polyphenolic compounds with signifi...

Treatment decision support for esophageal cancer based on PET/CT data using deep learning.

BMC medical informatics and decision making
BACKGROUND: Making precise treatment decisions in esophageal cancer is essential for enhancing patient outcomes and avoiding overtreatment. Traditional approaches relying on special features or shallow learning models often fail to capture the comple...

Subvisual imaging signals as biomarkers of impending lung metastasis: A multicenter pan-cancer study.

European journal of cancer (Oxford, England : 1990)
STUDY AIM: Early detection of distant metastases is crucial, but current imaging detects them only when radiographically visible. This study reported subvisual chest CT signals could serve as early biomarkers for impending lung metastasis before radi...

Automated Esophageal Cancer Staging From Free-Text Radiology Reports: Large Language Model Evaluation Study.

JMIR medical informatics
BACKGROUND: Accurate staging of esophageal cancer is crucial for determining prognosis and guiding treatment strategies, but manual interpretation of radiology reports by clinicians is prone to variability and limited accuracy, resulting in reduced s...

Application of artificial intelligence in esophageal surgery: a systematic review.

Journal of robotic surgery
The aim of this systematic review was to summarize and analyze the available literature on the application of artificial intelligence systems in esophageal surgery, focusing on anatomy recognition, instrument detection, and surgical phase recognition...