Author

Sivakumar Manickam

Observed name: Manickam, Sivakumar

Institution: Oman Dental College

Observed institution: Oman Dental College

ORCID: 0009-0006-5018-9384

Observed ORCID: 0009-0006-5018-9384

OpenAlex ID: A5148779300

Can Large Language Models (LLMs) be used to Generate FRCR Part 1 Physics Questions? A Multi-model Comparative Reviewer-based Study

2026 · Ebinesh Arulnathan, Shirou Masoodi, et al. · Clinical Radiology

Mapping the unseen: a data-driven visualization framework for curriculum analysis

2026 · Sivakumar Manickam, Mohamed Al Ismaili, et al. · Cogent Education

The Kaleidoscope Brain: Unravelling the Radiologic Signatures of Paediatric Metabolic Disorders

2026 · Manickam, Sivakumar · European Society of Radiology

Training minds for machine-age imaging: medical students’ needs, ethics and expectations for safe AI integration in radiology

2026 · Roshni Das, Ebinesh Arulnathan, et al. · The Royal College of Radiologists Open

Elevating the UK as the global leader in paediatric radiology AI: a national framework to reduce backlogs, standardise quality and transform children’s imaging services

2026 · Sivakumar Manickam, Shirou Masoodi, et al. · The Royal College of Radiologists Open

AI-assisted question generation for FRCR Part 1 Physics: evaluating the role of multi-model LLMs in high-stake radiology assessment design

2026 · Ebinesh Arulnathan, Shirou Masoodi, et al. · The Royal College of Radiologists Open

Integrating an LLM-based tool into emergency CT workflow: enhancing trainee vetting and protocolling in the NHS

2026 · Matthew Kueh, Ebinesh Arulnathan, et al. · The Royal College of Radiologists Open

Teaching with intelligence: a governance-led framework for AI-augmented MCQ generation in FRCR Part 2a preparation

2026 · Shirou Masoodi, Ebinesh Arulnathan, et al. · The Royal College of Radiologists Open

Augmenting emergency imaging decisions: performance of a custom large language-model decision-support system for SHOs in time-critical medical emergencies

2026 · Ebinesh Arulnathan, Praislin Gideon, et al. · The Royal College of Radiologists Open

Building the AI-ready radiologist: curriculum design, challenges and opportunities

2026 · Shirou Masoodi, Matthew Kueh, et al. · The Royal College of Radiologists Open

Clinician-led development of a PACS-native AI and reporting pipeline for neonatal cranial ultrasound in hypoxic-ischaemic encephalopathy to overcome inter-observer variability, time and resource constrains

2026 · Robert English, Rayya Naffa', et al. · The Royal College of Radiologists Open

Works count: 11

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