In recent years there has been increasing interest in AI applications in Plastic Surgery. I will report on a review I am conducting which explores the current legislative environment for AI research that uses patient image datasets and summarises key ethical considerations that are raised in existing AI burns care research. A basic framework for the reporting of burns image datasets that are used for AI research will also be suggested.
Speaker: Fiona Smith
I will discuss some work that I plan to do involving neurosymbolic AI on a biomedical knowledge graph to unveil the most likely paths by which these compounds execute their mechanism of action.
Speaker: Lauren DeLong
I will present ongoing work on building SaSSY-CLEVR, a heterogeneous benchmark suite which can serve as a common testing ground for different neuro-symbolic reasoners to compare their strengths and limitations. If time allows, I will also share a series of experiments to assess NeSy models on CLEVR-Hans3.
Speaker: Xuelong An
In this talk, I will discuss an ongoing project using knowledge-graph methods on CPRD data to detect people who are likely to have unexpected health problems (like falls or bleeding).
Speaker: Paola Galdi
We introduce our work using logical constraints to assist the training of neural networks via a theorem proving process and discuss plans for future work (funded by ELIAI).
Speakers: Matt Whyte and Mark Chevallier
In this talk, I will introduce a machine-learning-based tool for the Lean theorem prover that suggests relevant premises to a user interactively constructing a proof.
Speaker: Ramon Fernández Mir
In this study, I will explore the sequences of activities in patients presenting with COVID-19, assessing treatment efficiency between the first and second waves using process maps and metrics relative to recovery time.
Speaker: Konstantin Georgiev
In this talk we present our current work exploring stochastic block modelling and link prediction to forecast mortality and overcome some of the shortcomings present in existing approaches.
Speaker: Jorge Gaete Villegas
My research integrates data science and geriatric medicine to explore what different data sources and methods can tell us about frailty, a state of increased vulnerability to adverse health outcomes for individuals of the same chronological age.
Speaker: Lara Johnson
In this talk, I will discuss work on building ML model that takes into account prior knowledge of common activity patterns for the activity recognition task and uses the same model to forecast the individualized activity routine.
Speaker: Simon U