BACKGROUND: Patients with resectable esophageal squamous cell carcinoma (ESCC) receiving neoadjuvant immunotherapy (NIT) display variable treatment responses. The purpose of this study is to establish and validate a radiomics based on enhanced comput...
PURPOSE: This study was designed to investigate the prognostic significance of artificial intelligence (AI)-based quantification of myxoid stroma in patients undergoing esophageal squamous cell carcinoma (ESCC) surgery after neoadjuvant chemotherapy ...
This study aimed to establish a machine learning (ML) model for predicting hepatic metastasis in esophageal cancer. We retrospectively analyzed patients with esophageal cancer recorded in the Surveillance, Epidemiology, and End Results (SEER) databas...
BACKGROUND: Esophageal cancer remains a global challenge due to late diagnoses and limited treatments. Lymph node metastasis (LNM) is crucial for prognosis, yet traditional diagnostics fall short. Integrating radiomics and deep learning (DL) with CT ...
Medical & biological engineering & computing
38848031
Even though artificial intelligence and machine learning have demonstrated remarkable performances in medical image computing, their accountability and transparency level must be improved to transfer this success into clinical practice. The reliabili...
BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a deadly cancer with no clinically ideal biomarkers for early diagnosis. The objective of this study was to develop and validate a user-friendly diagnostic tool for early ESCC detection.
RATIONALE AND OBJECTIVES: Surgery in combination with chemo/radiotherapy is the standard treatment for locally advanced esophageal cancer. Even after the introduction of minimally invasive techniques, esophagectomy carries significant morbidity and m...
International journal of surgery (London, England)
38905510
BACKGROUND: Existing models do poorly when it comes to quantifying the risk of lymph node metastases (LNM). This study aimed to develop a machine-learning model for LNM in patients with T1 esophageal squamous cell carcinoma (ESCC).