Clinical AI

Applied Artificial Intelligence in Diagnostics & Modern Healthcare

Clinical Applications, Evaluation, Safety and Responsible Implementation

Applied, evidence-informed professional education in artificial intelligence across diagnostics, pathology and laboratory medicine, cancer care and precision medicine, generative AI, evaluation, patient safety, governance and responsible implementation.

Duration 6 hours Delivery Online professional continuing education Assessment 20 MCQs + one structured applied case | 70% overall pass threshold

The Royal College of Pathologists (UK)6 CPD credits

Australian College of Rural and Remote Medicine (ACRRM)6 Educational Activity CPD hours

Who it is for

Doctors and postgraduate medical trainees
Pathologists and professionals working in diagnostic services
Biomedical and clinical scientists
Laboratory professionals
Healthcare researchers and medical educators
Other healthcare professionals involved in diagnostics, cancer care, digital health, clinical research or implementation of AI-enabled systems

Learning outcomes

Explain fundamental concepts underlying artificial intelligence, machine learning, generative AI and large language models relevant to healthcare.
Identify appropriate applications and important limitations of AI across diagnostics, pathology, laboratory medicine, cancer care and wider healthcare workflows.
Evaluate the quality and clinical relevance of AI systems using concepts including validation, sensitivity, specificity, predictive value, bias, generalisability and dataset shift.
Recognise major patient-safety risks associated with AI, including hallucination, automation bias, inappropriate reliance on outputs and poor-quality or unrepresentative data.
Assess appropriate and inappropriate uses of generative AI and large language models in healthcare and research workflows.
Describe key ethical, privacy, governance, accountability, equity and human-oversight considerations when deploying AI in healthcare environments.
Apply a structured framework to critically assess whether an AI-enabled healthcare tool is appropriate for a particular clinical or organisational context.

Programme curriculum

Artificial Intelligence in Modern Healthcare | 55 minutes
AI in Diagnostics, Pathology & Laboratory Medicine | 60 minutes
AI in Cancer Care & Precision Medicine | 55 minutes
Generative AI for Healthcare Professionals | 55 minutes
Evaluating Medical AI: Evidence, Bias & Patient Safety | 65 minutes
Governance & Responsible AI Implementation | 60 minutes

Programme information

Award: OwnMind Labs Certificate of Completion
Course Director / Lead Faculty: Dr Shahroze Ahmed Khan, MD, PGDip Public Health, MRSPH
Contact: contact@ownmindlabs.com