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Multidimensional artificial intelligence decision support may improve precision and individualization in endoscopic submucosal dissection for early gastric cancerArtificial intelligence helps doctors treat early gastric cancer more precisely

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Key Takeaway
Note that multidimensional AI decision support may improve precision and individualization in ESD for early gastric cancer.

This systematic review evaluates the role of multidimensional artificial intelligence (AI) decision support across the entire endoscopic submucosal dissection (ESD) workflow for patients with early gastric cancer. The scope includes assessing technical pathways, feasibility of cross-stage integration, and identifying barriers to clinical translation.

The authors synthesize findings suggesting that AI is driving ESD diagnosis and treatment toward greater precision. A clinical decision support system (CDSS) may empower endoscopists to provide individualized precision therapy while addressing issues such as physician experience dependence, subjectivity, and high rates of missed diagnoses in the current workflow.

Several limitations currently hinder widespread implementation, including a scarcity of multicentre standardized datasets, limited model interpretability, and poor integration with existing clinical workflows. Future directions include multimodal data fusion, edge computing, and augmented reality to improve utility.

Clinical application is currently limited by the lack of specific efficacy rates in this review. While AI shows potential to reduce procedural variability, it remains a tool under evaluation rather than an established standard of care.

Doctors treating early gastric cancer face a tough challenge. The procedure used to remove the cancer, called endoscopic submucosal dissection (ESD), can be hard to perform perfectly every time. It often depends heavily on the experience of the doctor, which can lead to inconsistent results or missed diagnoses.

This review looks at how multidimensional artificial intelligence (AI) can step in as a decision support system. By using AI during the ESD workflow, doctors may get more precise guidance. The goal is to move away from subjective decisions and toward a system that provides consistent, high-quality care for every patient.

While the technology shows great promise for making surgery safer and more accurate, there are hurdles to clear first. Currently, researchers face a shortage of standardized data from multiple centers, and it can be hard to understand exactly how some AI models reach their conclusions. These factors mean that while AI is a powerful tool being evaluated right now, it is not yet a standard part of every clinic.

What this means for you:
AI tools could help doctors provide more consistent and precise treatment for early stomach cancer.

Common questions

How does AI help doctors treat stomach cancer?

AI acts as a decision support system during the endoscopic submucosal dissection (ESD) process. It helps doctors move toward more precise and individualized therapy by reducing the impact of human error, subjectivity, and variations in experience during the procedure.

Is AI currently used in every surgery for gastric cancer?

No, it is not yet a standard clinical tool. The review notes that AI is currently being evaluated and reviewed. There are still hurdles like limited model interpretability and a lack of standardized datasets before it can be fully integrated into everyday workflows.

What are the main challenges for using AI in these procedures?

The main barriers include a shortage of multicenter standardized datasets, difficulty in understanding how the models interpret data, and the challenge of integrating these complex systems into existing clinical workflows.

Study Details

Study typeSystematic review
EvidenceLevel 1
PublishedAug 2026
View Original Abstract ↓
Early diagnosis and treatment are essential for improving the prognosis of patients with gastric cancer. Endoscopic submucosal dissection (ESD) is the preferred minimally invasive treatment for early gastric cancer (EGC). Yet the entire diagnostic and therapeutic workflow depends heavily on the physician’s experience and is subject to strong subjectivity, procedural variability, and a high rate of missed diagnoses. Artificial intelligence (AI) offers a new approach to addressing these clinical pain points. This review systematically examines the progress of multidimensional AI decision support across the full ESD workflow for EGC. It evaluates the applicable scenarios and limitations of distinct technical pathways, discusses the feasibility of cross-stage integration of AI systems, and analyses the core barriers to clinical translation, including the scarcity of multicentre standardised datasets, limited model interpretability, and poor integration with clinical workflows. Finally, the review anticipates future directions, such as multimodal data fusion and the combination of edge computing with augmented reality technologies. AI is driving ESD diagnosis and treatment towards greater precision and intelligence. The development of an intelligent clinical decision support system (CDSS) that integrates diagnosis, treatment and follow-up may further empower endoscopists to deliver individualised precision therapy for early gastric cancer.
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