This README serves as an overview of the concepts and learning trajectory for a project aimed at understanding the role of AI in healthcare. It provides a structured outline of the key areas of focus and the educational goals associated with this learning endeavour.
AI has the potential to revolutionise healthcare by improving patient diagnosis, enhancing treatment plans, and enabling groundbreaking medical discoveries. This section explores the various domains in which AI can significantly impact healthcare.
- Recognise the importance of understanding clinical machine learning fundamentals for all stakeholders in the healthcare ecosystem.
- Gain knowledge about the origins and evolution of machine learning in healthcare.
- Understand common terms and definitions in machine learning.
- Define key terminology in the fields of machine learning, data science, and artificial intelligence.
- Identify the challenges and limitations of applying machine learning in healthcare.
- Learn the first principles for designing machine learning applications for healthcare.
As the image above illustrates the diverse scope of healthcare, highlighting the various sectors where AI can be implemented:
- Public Health: AI can support large-scale public health initiatives, improve disease surveillance, and enhance resource allocation.
- Global Health: AI technologies can address global health challenges by providing accessible and affordable healthcare solutions.
- Mental Health: AI can aid in the diagnosis and treatment of mental health disorders through advanced analytics and personalised therapy.
- Behavioral Health: AI tools can be used to monitor and support behavioral health interventions, improving patient outcomes.
- Dental Health: AI applications can enhance dental care through improved diagnostics, treatment planning, and patient management.
- Preventive Care: AI can play a significant role in preventive healthcare by predicting disease risk and promoting early interventions.
- Primary Care: AI can optimise primary care services, improving efficiency and patient care through decision support systems and automated workflows.
- Specialty Care: AI can support specialised medical fields with advanced diagnostic tools, personalised treatment plans, and innovative therapies.
- Emergency Care: AI can enhance emergency care by providing real-time decision support, triage, and predictive analytics to improve patient outcomes.
- Surgical Care: AI can assist in surgical procedures through robotics, image-guided surgery, and post-operative care management.
- Medical Diagnosis: The process by which healthcare professionals identify the nature of a patient's health condition or disease based on symptoms, medical history, physical examinations, and diagnostic tests or medical imaging.
- Medical Prognosis: The prediction or forecast of the expected course and outcome of a patient's health condition or disease, providing information about the likely progression, recovery, or outcome of the condition.
- Medical Treatment: The use of medical interventions, procedures, medications, or therapies by healthcare professionals to manage health conditions, injuries, or diseases, with the goal of improving patients' health and well-being.
- Medical Therapy: A systematic and structured approach to treating physical or mental health issues, including counselling, rehabilitation, and other interventions to help individuals recover from injuries, manage chronic conditions, or address psychological and emotional well-being.
Before delving deeper, it's crucial to understand the fundamental components of Artificial Intelligence (AI) to establish a solid foundation for further exploration.
To appreciate the context in which AI operates in healthcare, we will trace the historical evolution of AI, highlighting its origins, key milestones, and pivotal moments that have shaped its current prominence.
The integration of AI is a cornerstone of the ongoing digital transformation in healthcare. This section examines how digital transformation can contribute to achieving greater efficiency and improved patient care.
AI in healthcare is a double-edged sword, offering tremendous promise while also raising ethical and practical concerns. We will navigate this complex terrain by discussing the positive impacts of AI and identifying potential hurdles in its deployment.