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[The Current Situation and Prospects of the Application of Intelligent Diagnosis and Treatment Technology in the General Surgery]

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Specialty General Surgery
Date 2019 Jan 7
PMID 30612385
Citations 1
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Abstract

With the development of the times, a series of innovative intelligent diagnosis and treatment techniques have emerged, providing new strategies and means for disease diagnosis and treatment, which is helpful for promoting the development of general surgery in China. This article, combined with relevant literature at home and abroad, reviews the application of digital medical intelligent diagnosis and treatment technologies in general surgery,such as three-dimensional visualization,three-dimentional printing, mixed reality, molecular fluorescence imaging, artificial intelligence-imaging omics, abdominal surgery navigation and photoacoustic imaging. Three-dimentional visualization has changed the traditional "two-dimensional" disease diagnosis and treatment mode; three-dimentional printing of three-dimentional images is a leap-forward transition to stereoscopic physical models; mixed reality has broken the boundary between the digital virtual world and the physical real world, bringing technological innovation to traditional surgery; Indocyanine green molecular fluorescence imaging has achieved tumor boundary definition, micro or metastatic lesion detection and intraoperative real-time navigation at the molecular and cellular level; artificial intelligence-imaging omics can improve the accuracy of disease diagnosis and predict risk and efficacy; abdominal surgical navigation can improve the accuracy and safety of the operation; high precision-cross-scale photoacoustic microscopy can define the tumor boundary from the molecular, cellular and microvascular levels to guide the precise resection of the tumor; finally, this paper looks forward to the new direction of general surgery diagnosis and treatment represented by digital medicine and artificial intelligence.

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The Impact of Digital Transformation on Inpatient Care: Mixed Methods Study.

Koebe P, Bohnet-Joschko S JMIR Public Health Surveill. 2023; 9:e40622.

PMID: 37083473 PMC: 10163407. DOI: 10.2196/40622.