The speaker, Conor Judge, a medical consultant, and a senior lecturer, presents a potential solution to the imbalance between data collection and decision-making in healthcare. Conor introduces multimodal AI, which can interpret many forms of data, like humans. It has the potential to make healthcare delivery more efficient, freeing up time for medical practitioners to communicate with their patients.
Examples of single model AI are shared, including software that can autonomously report on chest x-rays, AI models that can diagnose and predict outcomes from eye conditions, and AI models that can pass US medical licensing exams. However, the speaker outlines that these models need to be used in conjunction with trained healthcare professionals. Medical multimodal AI has been shown to have potential in correctly diagnosing conditions and advising patients, and yet, the hurdles to its widespread use include the need for trust, explainability, and clinical trials. Conor emphasizes the need to combine AI with human compassion and understanding in healthcare.
