Dubai – AIJRF
The Artificial Intelligence Journalism for Research and Forecasting (AIJRF) has announced the launch of its first specialised training series on Artificial Intelligence in Healthcare and Medical Field, a multi-phase programme aimed at equipping healthcare professionals with the knowledge and tools to harness artificial intelligence in clinical and operational environments.
The applied training program, described by AIJRF as “a transformative step towards intelligent, data-driven healthcare,” is designed to help physicians, medical assistants, and healthcare specialists master AI technologies that enhance medical decision-making, improve efficiency, and build smarter healthcare systems.
According to AIJRF, the training series will consist of four progressive yet independent programmes, allowing participants either to enrol in a single course or complete all four levels for a comprehensive mastery of AI-driven medical applications. Each programme combines theoretical understanding with hands-on practice, introducing participants to at least ten practical AI tools and applications and culminating in an applied project for every trainee.
The curriculum begins with the fundamentals of artificial intelligence in medicine, advancing through the design of integrated medical databases and AI-based medical imaging and diagnostics, before concluding with a specialised module on developing custom AI medical agents for personalised and institutional healthcare use.
AIJRF said the programme aims to “bridge the gap between medicine and machine intelligence,” fostering collaboration between technology and clinical expertise to improve patient outcomes and operational effectiveness. In addition to the core programme, AIJRF will offer bespoke medical AI training solutions, tailored for hospitals, research institutions, and healthcare organisations seeking to implement artificial intelligence across their systems.
The programme aligns with the UAE’s broader ambition to integrate advanced technologies into healthcare, contributing to smarter, faster, and more connected medical ecosystems across the region.
4 Applied Training Courses
All training programmes are designed to be highly practical and application-focused, enabling participants to master no fewer than ten artificial intelligence tools and applications within each course. Every participant will also complete an individual applied project at the conclusion of each programme, ensuring hands-on experience and real-world implementation of the acquired skills.
Programme One: Fundamentals of Artificial Intelligence and Advanced Medical Services
Objective:
To provide physicians and healthcare practitioners with the essential understanding of AI technologies and their direct applications in modern medical environments.
Focus Areas:
- Understanding AI’s role in healthcare transformation
- Automating patient data collection and analysis
- Simplifying complex medical content using AI tools
- Mastering 15 key AI applications that enhance primary healthcare delivery
- Building confidence in daily AI-enabled decision-making
Key Learning Outcomes:
- Gain hands-on experience with tools such as ChatGPT-Health, IBM Watson Health, and Microsoft Azure AI Services
- Apply AI for patient record automation and triage systems
- Enhance clinical workflows through predictive analytics
- Develop communication strategies for patient engagement powered by AI
Target Participants:
General practitioners, medical assistants, hospital administrators, and early-career health informatics professionals.
Artificial Intelligence and Medical Databases
Programme Two: Artificial Intelligence in Building Integrated Medical Databases
Objective:
To train participants in designing, managing, and integrating AI-driven medical data ecosystems that form the backbone of intelligent hospitals and healthcare systems.
Focus Areas:
- Collecting, organising, and analysing large-scale medical data
- Designing smart databases that support real-time clinical decisions
- Creating virtual AI medical assistants for diagnostic and administrative support
Expected Outcomes:
- Participants will design a prototype of an integrated medical database
- Understand interoperability between healthcare systems and AI tools
- Gain expertise in data governance, ethics, and patient confidentiality within AI environments
- Mastering 15 key AI applications in Building Integrated Medical Databases
Tools and Platforms:
Google Cloud Healthcare AI, Amazon HealthLake, BioGPT, Power BI for Medical Analytics
Target Participants:
Healthcare data managers, medical researchers, hospital IT departments, and public health specialists.
AI and Medical Diagnosis
🩻 Programme Three: Artificial Intelligence in Medical Diagnosis and Image Analysis
Objective:
To enable participants to apply AI-powered computer vision and deep learning in analysing medical imagery for enhanced diagnostic accuracy.
Focus Areas:
- Leveraging AI for image-based disease detection (X-ray, MRI, CT)
- Training and validating AI models for radiology applications
- Understanding the ethical implications and accuracy standards of automated diagnosis
- Google MedLM for large medical language models
Practical Applications:
Participants will explore tools such as:
- Google MedLM for large medical language models
- BioMind and Radiology AI for clinical imaging analysis
- PyTorch Vision & TensorFlow Medical Frameworks for hands-on image classification
Outcomes:
- Ability to interpret AI-generated diagnostic results
- Build a small-scale AI imaging model for detecting early-stage abnormalities
- Integrate AI diagnostics into existing hospital imaging systems
- Mastering 15 key AI applications in in Medical Diagnosis and Image
Analysis Target Participants:
Radiologists, biomedical engineers, medical imaging specialists, and postgraduate researchers in medical technology.
Medical AI Agent
Programme Four: Medical AI Agent – Build Your Own Agent for Specialised Medical Services
Objective:
To empower each participant to develop a personalised AI agent capable of supporting their individual professional activities — from patient communication to real-time clinical assistance.
Focus Areas:
- Introduction to autonomous AI medical agents
- Building and training conversational AI tools tailored to healthcare practice
- Integrating medical APIs and knowledge bases for custom functionality
Outcomes:
- Each participant will create their own Medical AI Agent capable of performing selected tasks such as:
- Patient data entry and management
- Scheduling and reminders
- Initial symptom triage
- Continuous patient education and communication
Technologies Covered:
OpenAI API, LangChain for healthcare automation, Microsoft Copilot for Clinical Use, and GPT-based custom model training.
Target Participants:
Experienced clinicians, health innovators, and digital medicine specialists seeking to build bespoke AI solutions.
For registration please click here