Artificial Intelligence in Interventional Pulmonology.
Artificial intelligence (AI) is an exciting new technology poised to drastically improve the practice of medicine. Interventional pulmonology (IP) is particularly well situated to implement AI due to the variety of complex diagnostic and therapeutic techniques within its scope. By integrating AI int...
| Publicado en: | Therapeutic Advances in Pulmonary & Critical Care Medicine pp. 1 - 12 |
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| Autores principales: | , , , , , , |
| Formato: | review tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
7/14/2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=186678987&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 186678987 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 29768675 NKBK jtl: Therapeutic Advances in Pulmonary & Critical Care Medicine issn: 29768675 maglogo: N pubinfo: dt: 7/14/2025 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 186678987 186678987 186678987 10.1177/29768675251353390 186678987 ppf: 1 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Artificial Intelligence in Interventional Pulmonology. aug: au: Brower, David Sengupta, Sohawm Bhatt, Arjun N Allen, Steven Bechara, Rabih Islam, Shaheen Healy, William J affil: Medical College of Georgia School of Medicine, Augusta, GA, USA sug: subj: Artificial Intelligence Utilization Pulmonary Medicine Lung Diseases Therapy Lung Diseases Diagnosis Technology, Medical Artificial Intelligence Ethical Issues Image Interpretation, Computer Assisted Diagnosis, Computer Assisted Health Services Accessibility Bronchoscopy Bronchi Ultrasonography Pulmonologists Machine Learning Algorithms Deep Learning Endosonography Specimen Handling Methods Medical Informatics ab: Artificial intelligence (AI) is an exciting new technology poised to drastically improve the practice of medicine. Interventional pulmonology (IP) is particularly well situated to implement AI due to the variety of complex diagnostic and therapeutic techniques within its scope. By integrating AI into the field, the procedure planning and management of pulmonary disease should become easier, more accessible, and more effective. AI has already been implemented in the diagnostic techniques of navigational and virtual bronchoscopy, endobronchial ultrasound, and for the rapid onsite evaluation of pathological specimens. The goal of this review is to summarize recent utilization of AI in IP and to discuss the origins of the technology, ethical considerations, and future directions. Plain Language Summary: Artificial Intelligence in Interventional Pulmonology In this paper, we discuss advanced computer programs, commonly called Artificial Intelligence(AI), in the field of medicine that specializes in procedures performed in the lungs, called Interventional Pulmonology(IP). We begin by explaining that AI think in a similar way as human minds, but more powerfully. Then, we describe the origins of medical AI. Next, we begin our discussion on AI's use in IP today. First, we examine AI in bronchoscopy, which is sticking special camera through someone's to look into the inside of the lungs. As one might expect, knowing where the camera is exactly is in the lung is very difficult, and pulmonologists have developed AI that can help identify where the camera is in the lung. Another use for bronchoscopy is collecting samples from the lung to test diseases including cancer; however, knowing exactly where to go in the lung is difficult. Programs, broadly referred to as Navigational Bronchoscopy, use AI to create "maps" and then guide the doctor like a GPS. During bronchoscopies, pulmonologist can take look at parts of lung using a special tool called endobronchial ultrasound. These ultrasound pictures are hard to understand, so AI is being used to help interpret these images. Once the samples are collected, traditionally they are examined under a microscope to look for signs of disease. This is quite difficult, so AI have been made to help with this. We then discuss some of the ethical issues AI might face, as well as how we think AI will be used in the future in IP. pubtype: Academic Journal doctype: review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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