University College Lahore
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
Exploiting Unintended Feature Leakage in Collaborative Learning
Luca Melis, Congzheng Song, Emiliano De Cristofaro et al.
2019 · 87 Zit.
A standardised PRISMA-based protocol for systematic reviews of the scientific literature on Artificial Intelligence and education (AI&ED)
Christian M. Stracke, Irene‐Angelica Chounta, W. Holmes et al.
2023 · 17 Zit.
Attitudes and readiness to adopt artificial intelligence among healthcare practitioners in Pakistan’s resource-limited settings
Khaloud Tariq, Huma Tahir, Ushna Malik et al.
2025 · 4 Zit.
Perceptions of Medical Students towards Artificial Intelligence
Shazia Rizwan, Shahveir Rizwan, Muhammad Rizwan et al.
2025 · 3 Zit.
Hope and trust in diagnostic imaging contexts – Constituting technology and liminal patients
Susanne Holm, Frede Olesen
2024 · 2 Zit.
AI Integration in MCQ Development: Assessing Quality in Medical Education: A Systematic Review
Fizzah Ali, Hajra Talat
2024 · 2 Zit.
Ethics in the Digital Era
David Pastor-Escuredo
2020 · 1 Zit.
Big data has not revolutionised medicine – we need big theory alongside it
Peter V. Coveney, Edward R. Dougherty
2016 · 1 Zit.
75 Computer vision for object detection; machine learning-based identification of surgical equipment
Benedict Chan, Shirin Harandi, Daiana Bassi et al.
2019 · 1 Zit.
Evaluating the Diagnostic Accuracy of Artificial Intelligence in Periapical Radiographs
Adeel Haidar, Wajiha Alamgir, Irsam Haider et al.
2025 · 0 Zit.
To understand the risks posed by AI, follow the money
Tim O’Reilly, Ilan Strauss, Mariana Mazzucato et al.
2024 · 0 Zit.
74 A web based service for modular SMART on FHIR application development
Ziyang Dong, Qinyi Tang, Ralf Yap et al.
2019 · 0 Zit.
Artificial intelligence policy worldwide: a comparative analysis
Airlie Hilliard, Ayesha Gulley, Emre Kazim et al.
2026 · 0 Zit.
FROM INNOVATION TO REGULATION: ETHICAL GOVERNANCE OF AI IN TEACHING AND LEARNING
Sania Rehan, Zoya Faisal, Farzana Yousaf et al.
2026 · 0 Zit.
MORPHFED: Federated Learning for Cross-institutional Blood Morphology Analysis
Gabriel Ansah, Eden Ruffell, Delmiro Fernández-Reyes et al.
2026 · 0 Zit.