Mirza Mansoor Baig

Dr. Mirza Mansoor Baig

orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
19 June 2017 in Journal of Medical Systems
Verified
Journal Article
Closed access
PDF file
MBMirza Mansoor Baig
Mirza Mansoor Baig
Hamid GholamHosseiniHamid GholamHosseini
Hamid GholamHosseini
AMAasia A. Moqeem
Aasia A. Moqeem
FMFarhaan Mirza
Farhaan Mirza
MLMaria Lindén
Maria Lindén

15 January 2013 in Journal of Medical Systems
Verified
Journal Article
Closed access
PDF file
MBMirza Mansoor Baig
Mirza Mansoor Baig
Hamid GholamHosseiniHamid GholamHosseini
Hamid GholamHosseini

19 January 2013 in Medical & Biological Engineering & Computing
Verified
Journal Article
Closed access
PDF file
MBMirza Mansoor Baig
Mirza Mansoor Baig
Hamid GholamHosseiniHamid GholamHosseini
Hamid GholamHosseini
MCMartin J. Connolly
Martin J. Connolly

5 December 2014 in Australasian Physics & Engineering Sciences in Medicine
Verified
Journal Article
Closed access
PDF file
MBMirza Mansoor Baig
Mirza Mansoor Baig
Hamid GholamHosseiniHamid GholamHosseini
Hamid GholamHosseini
MCMartin J. Connolly
Martin J. Connolly

15 June 2019 in Journal of Medical Systems
Verified
Journal Article
Closed access
PDF file
MBMirza Mansoor Baig
Mirza Mansoor Baig
SAShereen Afifi
Shereen Afifi
HGHamid GholamHosseini
Hamid GholamHosseini
FMFarhaan Mirza
Farhaan Mirza

25 November 2024 in Applied Sciences
Verified
Journal Article
Open access
PDF file
MBMirza Mansoor Baig
Mirza Mansoor Baig
CHChristopher H Hobson
Christopher H Hobson
Hamid GholamHosseiniHamid GholamHosseini
Hamid GholamHosseini
Ehsan UllahEhsan Ullah
Ehsan Ullah
SAShereen Moataz Afifi
Shereen Moataz Afifi
The main aim of this study is to investigate the opportunities, challenges, and barriers in implementing generative artificial intelligence (Gen AI) in personalized patient care plans (PPCPs). This systematic review paper provides a comprehensive analysis of the current state, potential applications, and opportunities of Gen AI in patient care settings. This review aims to serve as a key resource for various stakeholders such as researchers, medical professionals, and data governance. We adopted the PRISMA review methodology and screened a total of 247 articles. After considering the eligibility and selection criteria, we selected 13 articles published between 2021 and 2024 (inclusive). The selection criteria were based on the inclusion of studies that report on the opportunities and challenges in improving PPCPs using Gen AI. We found that a holistic approach is required involving strategy, communications, integrations, and collaboration between AI developers, healthcare professionals, regulatory bodies, and patients. Developing frameworks that prioritize ethical considerations, patient privacy, and model transparency is crucial for the responsible deployment of Gen AI in healthcare. Balancing these opportunities and challenges requires collaboration between wider stakeholders to create a robust framework that maximizes the benefits of Gen AI in healthcare while addressing the key challenges and barriers such as explainability of the models, validation, regulation, and privacy integration with the existing clinical workflows.