Applications and Prospects of Artificial Intelligence-Assisted Endoscopic Ultrasound in Digestive System Diseases

Huang, Jia; Fan, Xiaofei; Liu, Wentian

doi:10.3390/diagnostics13172815

Cited by 7 publications

(1 citation statement)

References 81 publications

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“…With the gradual recognition of AI in healthcare, its superiority in the field of EUS has become increasingly evident. Research findings demonstrate that EUS-AI exhibits superiority, or at least equivalence, to conventional methods of diagnosis, prognosis, and quality control for subepithelial lesions, early esophageal cancer, early gastric cancer, and various pancreatic diseases, including pancreatic cystic lesions, autoimmune pancreatitis, and pancreatic cancer [93]. The implementation of EUS-AI has opened up new avenues for individualized precision medicine while introducing innovative approaches to diagnosing and treating digestive diseases.…”

Section: Medical Imagingmentioning

confidence: 98%

Transformative Potential of AI in Healthcare: Definitions, Applications, and Navigating the Ethical Landscape and Public Perspectives

Bekbolatova,

Mayer,

Ong

et al. 2024

Healthcare

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Artificial intelligence (AI) has emerged as a crucial tool in healthcare with the primary aim of improving patient outcomes and optimizing healthcare delivery. By harnessing machine learning algorithms, natural language processing, and computer vision, AI enables the analysis of complex medical data. The integration of AI into healthcare systems aims to support clinicians, personalize patient care, and enhance population health, all while addressing the challenges posed by rising costs and limited resources. As a subdivision of computer science, AI focuses on the development of advanced algorithms capable of performing complex tasks that were once reliant on human intelligence. The ultimate goal is to achieve human-level performance with improved efficiency and accuracy in problem-solving and task execution, thereby reducing the need for human intervention. Various industries, including engineering, media/entertainment, finance, and education, have already reaped significant benefits by incorporating AI systems into their operations. Notably, the healthcare sector has witnessed rapid growth in the utilization of AI technology. Nevertheless, there remains untapped potential for AI to truly revolutionize the industry. It is important to note that despite concerns about job displacement, AI in healthcare should not be viewed as a threat to human workers. Instead, AI systems are designed to augment and support healthcare professionals, freeing up their time to focus on more complex and critical tasks. By automating routine and repetitive tasks, AI can alleviate the burden on healthcare professionals, allowing them to dedicate more attention to patient care and meaningful interactions. However, legal and ethical challenges must be addressed when embracing AI technology in medicine, alongside comprehensive public education to ensure widespread acceptance.

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Section: Medical Imagingmentioning

confidence: 98%

Transformative Potential of AI in Healthcare: Definitions, Applications, and Navigating the Ethical Landscape and Public Perspectives

Bekbolatova,

Mayer,

Ong

et al. 2024

Healthcare

View full text Add to dashboard Cite

show abstract

The diagnostic value of endoscopic ultrasound for esophageal subepithelial lesions: A review

Li,

Shao,

et al. 2024

Medicine

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Esophageal subepithelial lesions (ESELs) encompass a variety of diseases, including leiomyoma, granular cell tumors, hemangioma, lipoma, stromal tumors, leiomyosarcoma, schwannoma, neuroendocrine tumors and more. These lesions often present asymptomatically, leading to a generally low clinical diagnosis rate. Common imaging techniques for diagnosing ESELs include conventional endoscopy, spiral computed tomography, and endoscopic ultrasound (EUS). Among these, EUS is currently regarded as one of the most accurate methods for diagnosing ESELs. In recent years, EUS has increasingly been combined with advanced technologies such as artificial intelligence, submucosal saline injection, high-frequency impedance measurement, and enhanced imaging to improve diagnostic accuracy and reduce missed diagnoses. This article reviews the application and recent advancements of EUS in diagnosing esophageal submucosal lesions.

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Progress in artificial intelligence assisted digestive endoscopy diagnosis of digestive system diseases

Zhao,

Liu

2024

WCJD

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Applications and Prospects of Artificial Intelligence-Assisted Endoscopic Ultrasound in Digestive System Diseases

Cited by 7 publications

References 81 publications

Transformative Potential of AI in Healthcare: Definitions, Applications, and Navigating the Ethical Landscape and Public Perspectives

Transformative Potential of AI in Healthcare: Definitions, Applications, and Navigating the Ethical Landscape and Public Perspectives

The diagnostic value of endoscopic ultrasound for esophageal subepithelial lesions: A review

Progress in artificial intelligence assisted digestive endoscopy diagnosis of digestive system diseases

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