The COVID-19 pandemic is running its apocalyptic course around the world. One thing is certain in the midst of total uncertainty and utter chaos: SARS-CoV-2 is a very daunting enemy and we remain totally subjugated by these viral overlords. It is easy, therefore, for we humans to lose patience and become careless as well as to decrease capacity for resilience. We need to regain our composure and to be defiant in order to for us to prevail this human vs virus struggle.
A major part of this resilience and defiance is continue our work in adoption and deployment of artificial intelligence concepts and projects in clinical medicine. Here are key takeaways from the second day (11th November 2020) of AIMed Pediatrics webinar in collaboration with the international society of Pediatric Innovation (iSPI).
- The AI in medicine and healthcare journey for anyone who is interested should be a personal and evolving one and can range from on-line courses to formal education. Simply “jump in!”
- Natural language processing (NLP) tools such as chatbots, virtual assistants, conversational agents, and others are already here and available for use in healthcare, but remains under-leveraged.
- A cognitive layer and design thinking can be added to NLP tools for more creative use as well as human emotions such as empathy.
- Patients and families are ahead of us in the adoption of emerging technologies including NLP tools and provider organizations need to catch up.
- Understanding cultural and behavioral differences in cultures is much more important than the languages themselves in accommodating NLP tools in various cultures.
- A special synergy between humans and machines in NLP can leverage each others’ strengths as patients and families sometimes are more comfortable with machines (feeling these are less judgmental).
- For ICU related data science projects, important data issues include data from relevant sources, time series registration, and biomedical definitions.
- Analogy between AI and music: Model is the musical instrument, data are the notes, and we are the musicians and composers and all of this can lead to beautiful AI music in the near future.
- AI can be used for information filtration and dissemination for pediatric clinicians to streamline the right information to the right people at the right time with the use of crowd sourcing.
- AI will be capable of generating new knowledge in one’s most clinical domains by deciphering signals in the noise (such as cluster analysis in unsupervised learning).
- A co-creation model of AI projects need to involve both the clinicians as well as the data scientists for the most robust dividends for the projects.
- It is not enough to bring clinicians and data scientists together but there is a dire need for both sides to learn each others’ knowledge and vocabulary.
- Our AI strategic aim should include using its tools to decrease the inequities in children’s healthcare delivery.
- Artificial intelligence as a resource to improve healthcare in children is absolutely essential as well as ethically necessary for the future trajectory of pediatric healthcare.
- We should consider the ethics of not having AI tools in children to optimize the quality of their care by balancing a sense of urgency with a commitment to persevere.