Development and evaluation of a double-check support system using artificial intelligence in endoscopic screening for gastric cancer

2021 ◽  
Author(s):  
Hirotaka Oura ◽  
Tomoaki Matsumura ◽  
Mai Fujie ◽  
Tsubasa Ishikawa ◽  
Ariki Nagashima ◽  
...  
2020 ◽  
Vol 91 (6) ◽  
pp. AB582
Author(s):  
Hirotaka Oura ◽  
Tomoaki Matsumura ◽  
Tatsuya Kaneko ◽  
Mamoru Tokunaga ◽  
Yushi Imai ◽  
...  

2020 ◽  
Vol 91 (6) ◽  
pp. AB49
Author(s):  
Hirotaka Oura ◽  
Tomoaki Matsumura ◽  
Tatsuya Kaneko ◽  
Mamoru Tokunaga ◽  
Yushi Imai ◽  
...  

2021 ◽  
Vol 27 (22) ◽  
pp. 2979-2993
Author(s):  
Yu-Jer Hsiao ◽  
Yuan-Chih Wen ◽  
Wei-Yi Lai ◽  
Yi-Ying Lin ◽  
Yi-Ping Yang ◽  
...  

2020 ◽  
Author(s):  
IF Cherciu Harbiyeli ◽  
IM Cazacu ◽  
ET Ivan ◽  
MS Serbanescu ◽  
B Hurezeanu ◽  
...  

2020 ◽  
Author(s):  
Avishek Choudhury

UNSTRUCTURED Objective: The potential benefits of artificial intelligence based decision support system (AI-DSS) from a theoretical perspective are well documented and perceived by researchers but there is a lack of evidence showing its influence on routine clinical practice and how its perceived by care providers. Since the effectiveness of AI systems depends on data quality, implementation, and interpretation. The purpose of this literature review is to analyze the effectiveness of AI-DSS in clinical setting and understand its influence on clinician’s decision making outcome. Materials and Methods: This review protocol follows the Preferred Reporting Items for Systematic Reviews and Meta- Analyses reporting guidelines. Literature will be identified using a multi-database search strategy developed in consultation with a librarian. The proposed screening process consists of a title and abstract scan, followed by a full-text review by two reviewers to determine the eligibility of articles. Studies outlining application of AI based decision support system in a clinical setting and its impact on clinician’s decision making, will be included. A tabular synthesis of the general study details will be provided, as well as a narrative synthesis of the extracted data, organised into themes. Studies solely reporting AI accuracy an but not implemented in a clinical setting to measure its influence on clinical decision making were excluded from further review. Results: We identified 8 eligible studies that implemented AI-DSS in a clinical setting to facilitate decisions concerning prostate cancer, post traumatic stress disorder, cardiac ailment, back pain, and others. Five (62.50%) out of 8 studies reported positive outcome of AI-DSS. Conclusion: The systematic review indicated that AI-enabled decision support systems, when implemented in a clinical setting and used by clinicians might not ensure enhanced decision making. However, there are very limited studies to confirm the claim that AI based decision support system can uplift clinicians decision making abilities.


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