The Application of Mixed Reality in Bronchoscopy Simulation Training: A Feasibility Study

Okachi, Shotaro; Sakurai, Manami; Matsui, Toshinori; Itō, Takayasu; Matsuzawa, Reiko; Morise, Masahiro; Wakahara, Keiko; Ishii, Makoto; Fujiwara, Michitaka

doi:10.1177/15533506231160201

Cited by 1 publication

(1 citation statement)

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“…The results showed that the group receiving real-time feedback from the artificial intelligence exhibited significantly higher performance in segment identification. Furthermore, from an educational perspective, augmented reality has gained attention in recent years for its ability to enhance motivation and improve training efficiency [27]. It is foreseeable that integrating artificial intelligence technology with bronchial anatomy identification into augmented and virtual reality will lead to more efficient bronchoscopy training methods in the future.…”

Section: Artificial Intelligence In Endoscopymentioning

confidence: 99%

Artificial intelligence in interventional pulmonology

Ishiwata,

Yasufuku

2023

Current Opinion in Pulmonary Medicine

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Purpose of review In recent years, there has been remarkable progress in the field of artificial intelligence technology. Artificial intelligence applications have been extensively researched and actively implemented across various domains within healthcare. This study reviews the current state of artificial intelligence research in interventional pulmonology and engages in a discussion to comprehend its capabilities and implications. Recent findings Deep learning, a subset of artificial intelligence, has found extensive applications in recent years, enabling highly accurate identification and labeling of bronchial segments solely from intraluminal bronchial images. Furthermore, research has explored the use of artificial intelligence for the analysis of endobronchial ultrasound images, achieving a high degree of accuracy in distinguishing between benign and malignant targets within ultrasound images. These advancements have become possible due to the increased computational power of modern systems and the utilization of vast datasets, facilitating detections and predictions with greater precision and speed. Summary Artificial intelligence integration into interventional pulmonology has the potential to enhance diagnostic accuracy and patient safety, ultimately leading to improved patient outcomes. However, the clinical impacts of artificial intelligence enhanced procedures remain unassessed. Additional research is necessary to evaluate both the advantages and disadvantages of artificial intelligence in the field of interventional pulmonology.

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Section: Artificial Intelligence In Endoscopymentioning

confidence: 99%