Evidence map›Paper›PMID 39165454›Full record

ReviewCureus2024

Emerging Applications of Picture Archiving and Communication Systems and Their Impact on Research and Education: A Literature Review.

Albert P Varghese, Shreya Naik, Syed Asrar Ul Haq Andrabi, Anurag Luharia, Suhas Tivaskar, Jubin John, Gaurav V Mishra, Ashish Uke, Sweta G Pisulkar, Mayur Wanjari

Abstract readReview
In one paragraph

Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Albert P VargheseDepartment of Radiology, Datta Meghe Institute of Higher Education and Research, Wardha, IND.
Shreya NaikDepartment of Radiology, Datta Meghe Institute of Higher Education and Research, Wardha, IND.
Syed Asrar Ul Haq AndrabiDepartment of Radiology, Datta Meghe Institute of Higher Education and Research, Wardha, IND.
Anurag LuhariaDepartment of Radiology, Datta Meghe Institute of Higher Education and Research, Wardha, IND.
Suhas TivaskarDepartment of Radiology, Datta Meghe Institute of Higher Education and Research, Wardha, IND.
Jubin JohnDepartment of Radiology, Datta Meghe Institute of Higher Education and Research, Wardha, IND.
Gaurav V MishraDepartment of Radiology, Datta Meghe Institute of Higher Education and Research, Wardha, IND.
Ashish UkeDepartment of Radiation Oncology, Datta Meghe Institute of Higher Education and Research, Wardha, IND.
Sweta G PisulkarDepartment of Prosthodontics and Crown and Bridge, Sharad Pawar Dental College, Wardha, IND.
Mayur WanjariDepartment of Research and Development, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent times, technological advancements have remarkably improved picture archiving and communication system (PACS) capabilities beyond their conventional use in radiology departments. Researchers and instructors have started employing PACS functionalities to improve medical research processes, promote interdisciplinary collaborations, and facilitate learning. To illustrate this point further, the PACS enables researchers to handle and analyze huge amounts of imaging data with superior precision and speed, supporting innovative studies in areas like disease progression, treatment outcomes, and imaging modalities. Moreover, a PACS integrated with artificial intelligence (AI) algorithms leads to significant improvements in image processing, diagnostic accuracy, and personalized treatment, thus marking a new approach to medical imaging. The PACS supported by AI is mostly transformative since they allow for improved early disease detection capabilities as well as automated image processing and decision assistance, which increase diagnostic accuracy and clinical outcomes. Such systems can rapidly process large quantities of visual data with an accuracy rate surpassing earlier endeavors. In medical research, however, combining PACS with AI allows challenging imaging datasets to be examined, thereby making findings that were not previously possible. The capacity to combine imaging outcomes with clinical information is valuable for medical students and professionals in the field of education. They can access extensive medical image collections and case studies using PACS. This link is critical for teaching and learning as it allows students to interact with concrete events and improve their diagnostic accuracy in a controlled environment. This review discusses how the PACS affects educational courses and clinical outcomes based on the available literature. Our aim was not only to outline recent research or developments but also to present a comprehensive overview regarding the growing role played by PACS in the modern healthcare system and academics. Similarly, we look at the challenges and opportunities associated with the wide adoption of PACS, highlighting possible future areas of study or teaching methodologies. Issues such as data security, interoperability, and the need for defined protocols are included to give an exhaustive understanding of what PACS can and cannot do. Through this study, we stress PACS's revolutionary potential in advancing research methodology and educational practices, eventually contributing to enhanced patient care and knowledge dissemination in healthcare areas. The continual growth of PACS technology and its applications is expected to reshape the landscape of medical research and education, making it a vital component in the quest for medical excellence. By knowing the present trends and future potential, stakeholders in healthcare and education may better employ PACS to reach their objectives and boost overall results.

Indexed as

medical communicationnetworkingpacsradiodiagnosisradiology

Identifiers

PMID39165454
PMCPMC11335171

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.