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p-Index From 2021 - 2026
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This Author published in this journals
All Journal Journal Of World Science International Journal of Multidisciplinary Sciences and Arts Jurihum
Shah Zeb
Washington University of Science and Technology, 2900 Eisenhower Ave, Alexandria, VA
Computer Science & IT Economics, Econometrics & Finance Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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Health Informatics in the 21st Century: The Role of Data in Advancing Healthcare Mohammed Javeedullah; Shah Zeb
JURIHUM : Jurnal Inovasi dan Humaniora Vol. 1 No. 3 (2023): JURIHUM : Jurnal Riset dan Humaniora
Publisher : CV. Shofanah Media Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Health informatics is changing healthcare by joining technology, data study and digital solutions to support patient care, streamline working methods and fight public health problems. Better ways of care coordination and decision-making are possible now thanks to Electronic Health Records (EHRs), Health Information Exchange (HIE) and interoperability. Artificial Intelligence (AI), Machine Learning (ML) and big data analytics are used to optimize healthcare by enabling customized treatment and making predictions about health problems. Even so, worries about data privacy, cybersecurity and healthcare professionals not wanting to change still cause problems. Trust and fairness in health informatics rely heavily on following ethical and legal rules such as getting patient permission and staying within the limits set by regulators. Health informatics is playing a larger part in public health by making disease surveillance and managing the health of populations more effective. For health informatics to achieve its maximum effects in changing healthcare, it must address these issues.
Ai-Driven Robotics and Automation: The Evolution of Human-Machine Collaboration Shahrukh Khan Lodhi; Shah Zeb
Journal of World Science Vol. 4 No. 4 (2025): Journal of World Science
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jws.v4i4.1389

Abstract

AI-driven robotics has transformed industries through enhanced automation, yet challenges like ethical dilemmas, workforce displacement, and cybersecurity gaps persist. While prior research focused on functional applications, emotional intelligence and bio-inspired designs remain underexplored. This study examines the integration of emotionally intelligent and bio-inspired robots into human-machine collaboration, evaluates ethical governance frameworks, and proposes solutions for global regulatory harmonization. A mixed-method approach was employed, combining systematic literature reviews of 72 peer-reviewed articles (2014–2024) and case studies of AI robotics in healthcare, manufacturing, and agriculture. Data were analyzed via thematic coding and SWOT analysis. Key innovations include socially intelligent robots for elderly care, BCIs for neural-controlled prosthetics, and swarm robotics for precision agriculture. Ethical challenges like bias in hiring algorithms and accountability gaps in autonomous systems were identified, necessitating transparent AI audits. The research advocates for adaptive regulatory models to balance innovation with ethical safeguards, emphasizing human-centric collaboration. It calls for international standards to address bias, cybersecurity, and liability, offering a roadmap for policymakers and industries to harness AI robotics responsibly.
Healing with Intelligence: A Review of AI-Enabled Healthcare Solutions Shah Zeb
International Journal of Multidisciplinary Sciences and Arts Vol. 4 No. 3 (2025): International Journal of Multidisciplinary Sciences and Arts, Article July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v4i3.6839

Abstract

Artificial intelligence (AI) is taking the healthcare field by storm as healthcare providers adopt its use to inform data-based decisions, improve clinical decision-making, and make their operations more efficient. This review discusses the fundamentals of AI, including machine learning, deep learning, and natural language processing technologies and how they can be applied to diagnostics, individualized treatment, remote patient monitoring, hospital operations, and population health monitoring. The strengths of AI are the ability to identify early disease, custom care plans, and precognitive analysis to direct resources. Nevertheless, integration in healthcare systems is stalled by risk of having biased algorithms, data privacy, interoperability, and changing demands of regulatory guidelines. A solution to such barriers is interdisciplinary: combining multiple views to develop and validate the models legitimately, with transparency and trustworthiness. Future trends, such as explainable AI, federated learning and integration of the robots aim at a more flexible and patient-centered future. After all, the best role that AI can play is to augment human expertise by providing more precise, proactive and fair care but without losing that critical human touch in healthcare.
Co-Authors Mohammed Javeedullah Shahrukh Khan Lodhi