Artificial intelligence and the radiologist: the future in the Armed Forces Medical Services. Issue 4 (31st January 2019)
- Record Type:
- Journal Article
- Title:
- Artificial intelligence and the radiologist: the future in the Armed Forces Medical Services. Issue 4 (31st January 2019)
- Main Title:
- Artificial intelligence and the radiologist: the future in the Armed Forces Medical Services
- Authors:
- Sen, Debraj
Chakrabarti, R
Chatterjee, S
Grewal, D S
Manrai, K - Abstract:
- Abstract : Artificial intelligence (AI) involves computational networks (neural networks) that simulate human intelligence. The incorporation of AI in radiology will help in dealing with the tedious, repetitive, time-consuming job of detecting relevant findings in diagnostic imaging and segmenting the detected images into smaller data. It would also help in identifying details that are oblivious to the human eye. AI will have an immense impact in populations with deficiency of radiologists and in screening programmes. By correlating imaging data from millions of patients and their clinico-demographic-therapy-morbidity-mortality profiles, AI could lead to identification of new imaging biomarkers. This would change therapy and direct new research. However, issues of standardisation, transparency, ethics, regulations, training, accreditation and safety are the challenges ahead. The Armed Forces Medical Services has widely dispersed units, medical echelons and roles ranging from small field units to large static tertiary care centres. They can incorporate AI-enabled radiological services to subserve small remotely located hospitals and detachments without posted radiologists and ease the load of radiologists in larger hospitals. Early widespread incorporation of information technology and enabled services in our hospitals, adequate funding, regular upgradation of software and hardware, dedicated trained manpower to manage the information technology services and train staff, andAbstract : Artificial intelligence (AI) involves computational networks (neural networks) that simulate human intelligence. The incorporation of AI in radiology will help in dealing with the tedious, repetitive, time-consuming job of detecting relevant findings in diagnostic imaging and segmenting the detected images into smaller data. It would also help in identifying details that are oblivious to the human eye. AI will have an immense impact in populations with deficiency of radiologists and in screening programmes. By correlating imaging data from millions of patients and their clinico-demographic-therapy-morbidity-mortality profiles, AI could lead to identification of new imaging biomarkers. This would change therapy and direct new research. However, issues of standardisation, transparency, ethics, regulations, training, accreditation and safety are the challenges ahead. The Armed Forces Medical Services has widely dispersed units, medical echelons and roles ranging from small field units to large static tertiary care centres. They can incorporate AI-enabled radiological services to subserve small remotely located hospitals and detachments without posted radiologists and ease the load of radiologists in larger hospitals. Early widespread incorporation of information technology and enabled services in our hospitals, adequate funding, regular upgradation of software and hardware, dedicated trained manpower to manage the information technology services and train staff, and cyber security are issues that need to be addressed. … (more)
- Is Part Of:
- BMJ military health. Volume 166:Issue 4(2020)
- Journal:
- BMJ military health
- Issue:
- Volume 166:Issue 4(2020)
- Issue Display:
- Volume 166, Issue 4 (2020)
- Year:
- 2020
- Volume:
- 166
- Issue:
- 4
- Issue Sort Value:
- 2020-0166-0004-0000
- Page Start:
- 254
- Page End:
- 256
- Publication Date:
- 2019-01-31
- Subjects:
- artificial intelligence (AI) -- machine learning -- deep learning -- radiology -- Armed Forces Medical Services (AFMS)
Medicine, Military -- Periodicals
Military hygiene -- Periodicals
355.345 - Journal URLs:
- http://www.bmj.com/archive ↗
https://militaryhealth.bmj.com/ ↗ - DOI:
- 10.1136/jramc-2018-001055 ↗
- Languages:
- English
- ISSNs:
- 2633-3767
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 25571.xml