AIMC Topic: Esophageal Neoplasms

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Artificial neural networks as a prognostic tool using hyperspectral imaging on pretherapeutic histopathological specimens of esophageal adenocarcinoma.

Journal of cancer research and clinical oncology
PURPOSE: The integration of artificial intelligence (AI) with hyperspectral imaging (HSI) offers a promising avenue for improving pre-therapeutic prognosis, a key factor in optimizing cancer treatment strategies. This study explores the potential of ...

Profiling the Chemical Exposomic Landscape of Esophageal Squamous Cell Carcinoma.

Environmental science & technology
While the cancer genome is well-studied, the nongenetic exposome of cancer remains elusive, particularly for regionally prevalent cancers with poor prognosis. Here, by employing a combined knowledge- and data-driven strategy, we profile the chemical ...

Integrative single-cell and bulk transcriptomic analysis reveals the landscape of T cell mitotic catastrophe associated genes in esophageal squamous cell carcinoma.

Human genomics
BACKGROUND: Mitotic catastrophe (MC) is a well-recognized endogenous mechanism of tumor cell death, characterized as a delayed cell death process associated with aberrant mitosis. However, its prognostic significance in the context of intratumoral he...

Environmental exposure to perfluorooctane sulfonate and its role in esophageal cancer progression: a comprehensive bioinformatics and experimental study.

Scientific reports
Esophageal cancer (ESCA) is a significant malignancy with rising global incidence rates and considerable impacts on patient survival and quality of life. Current diagnostic and therapeutic strategies face limitations, necessitating research into its ...

Screening, Validation, and Machine Learning-Based Evaluation of Serum Protein Biomarkers for Esophageal Squamous Cell Carcinoma Based on Single-Cell Subtype-Specific Genes.

Journal of proteome research
Cellular heterogeneity of epithelial cells and fibroblasts is critical in esophageal squamous cell carcinoma development (ESCC). Identifying dysregulated subtype-specific genes in these cells is essential for early diagnosis and treatment. In this st...

Quantitative image analysis of the extracellular matrix of esophageal squamous cell carcinoma and high grade dysplasia via two-photon microscopy.

Scientific reports
Squamous cell carcinoma (SCC) and high-grade dysplasia (HGD) are two different pathological entities; however, they sometimes share similarities in histological structure depending on the context. Thus, distinguishing between the two may require care...

Development and validation of a nomogram model to predict postoperative delirium after resection of esophageal cancer.

Scientific reports
The study aimed to establish and validate a nomogram model to predict postoperative delirium (POD) among esophageal cancer resection patients. Clinical data of 396 patients with esophageal cancer who underwent esophagectomy from November 2020 to June...

Developing a machine-learning model to enable treatment selection for neoadjuvant chemotherapy for esophageal cancer.

Scientific reports
Although neoadjuvant chemotherapy with docetaxel + cisplatin + 5-fluorouracil (CF) has been the standard treatment for stage II and III esophageal cancers, it is associated with severe adverse events caused by docetaxel. Consequently, this study aime...

A ubiquitous and interoperable deep learning model for automatic detection of pleomorphic gastroesophageal lesions.

Scientific reports
In recent years, artificial intelligence (AI) has been widely explored to enhance capsule endoscopy (CE), with the goal of improving the efficiency of the reading process. While most AI models have been developed for small bowel and colon analysis, t...