The landscape of gastrointestinal endoscopy continues to evolve as new technologies and techniques become available.The advent of image-enhanced and magnifying endoscopies has highlighted the step toward perfecting en...The landscape of gastrointestinal endoscopy continues to evolve as new technologies and techniques become available.The advent of image-enhanced and magnifying endoscopies has highlighted the step toward perfecting endoscopic screening and diagnosis of gastric lesions.Simultaneously,with the development of convolutional neural network,artificial intelligence(AI)has made unprecedented breakthroughs in medical imaging,including the ongoing trials of computer-aided detection of colorectal polyps and gastrointestinal bleeding.In the past demi-decade,applications of AI systems in gastric cancer have also emerged.With AI’s efficient computational power and learning capacities,endoscopists can improve their diagnostic accuracies and avoid the missing or mischaracterization of gastric neoplastic changes.So far,several AI systems that incorporated both traditional and novel endoscopy technologies have been developed for various purposes,with most systems achieving an accuracy of more than 80%.However,their feasibility,effectiveness,and safety in clinical practice remain to be seen as there have been no clinical trials yet.Nonetheless,AI-assisted endoscopies shed light on more accurate and sensitive ways for early detection,treatment guidance and prognosis prediction of gastric lesions.This review summarizes the current status of various AI applications in gastric cancer and pinpoints directions for future research and clinical practice implementation from a clinical perspective.展开更多
As industry progresses toward intelligent production and development,on-site workers that perform repetitive tasks will be replaced by intelligent machines.Currently,automation applications still have the following pr...As industry progresses toward intelligent production and development,on-site workers that perform repetitive tasks will be replaced by intelligent machines.Currently,automation applications still have the following problems:(1)on-site personnel are required to line up the workpieces before a robot arm can pick it up;(2)the trajectory generated by offline programming software must be adjusted by on-site personnel in accordance with the processing results;and(3)because of workpiece positioning errors and tool wear,achieving acceptable processing results is difficult.This study developed intelligent application modules that solve the aforementioned automation application problems.These modules predict processing quality,generate trajectory,enable robot arms to load and unload randomly positioned workpieces,and automatically calibrate the system.An automatic gear edge grinding system was developed by integrating each module;the system increases the processing efficiency and solves the current problem of manual grinding being required after gear processing.展开更多
文摘The landscape of gastrointestinal endoscopy continues to evolve as new technologies and techniques become available.The advent of image-enhanced and magnifying endoscopies has highlighted the step toward perfecting endoscopic screening and diagnosis of gastric lesions.Simultaneously,with the development of convolutional neural network,artificial intelligence(AI)has made unprecedented breakthroughs in medical imaging,including the ongoing trials of computer-aided detection of colorectal polyps and gastrointestinal bleeding.In the past demi-decade,applications of AI systems in gastric cancer have also emerged.With AI’s efficient computational power and learning capacities,endoscopists can improve their diagnostic accuracies and avoid the missing or mischaracterization of gastric neoplastic changes.So far,several AI systems that incorporated both traditional and novel endoscopy technologies have been developed for various purposes,with most systems achieving an accuracy of more than 80%.However,their feasibility,effectiveness,and safety in clinical practice remain to be seen as there have been no clinical trials yet.Nonetheless,AI-assisted endoscopies shed light on more accurate and sensitive ways for early detection,treatment guidance and prognosis prediction of gastric lesions.This review summarizes the current status of various AI applications in gastric cancer and pinpoints directions for future research and clinical practice implementation from a clinical perspective.
基金express gratitude toward the Technology Development Program of the Ministry of Economic Affairs and the Industrial Technology Research Institution for providing funding and support.
文摘As industry progresses toward intelligent production and development,on-site workers that perform repetitive tasks will be replaced by intelligent machines.Currently,automation applications still have the following problems:(1)on-site personnel are required to line up the workpieces before a robot arm can pick it up;(2)the trajectory generated by offline programming software must be adjusted by on-site personnel in accordance with the processing results;and(3)because of workpiece positioning errors and tool wear,achieving acceptable processing results is difficult.This study developed intelligent application modules that solve the aforementioned automation application problems.These modules predict processing quality,generate trajectory,enable robot arms to load and unload randomly positioned workpieces,and automatically calibrate the system.An automatic gear edge grinding system was developed by integrating each module;the system increases the processing efficiency and solves the current problem of manual grinding being required after gear processing.
