Health & bioscience

This paper argues that the technical landscape of clinical machine learning is shifting in ways that destabilize these pervasive assumptions about the nature and causes of algorithmic bias. On the one hand, the dominant paradigm in clinical machine learning is specialist in the sense that models are trained on biomedical datasets for particular clinical tasks such as diagnosis and treatment...

DNA-Encoded Chemical Libraries (DELs) have emerged as efficient and cost-effective ligand discovery tools, which enable the generation of protein-ligand interaction data of unprecedented size. In this article, we present an approach that combines DEL screening and instance-level deep learning modeling to identify tumor-targeting ligands against Carbonic Anhydrase IX (CAIX), a clinically...

This thesis presents a novel approach to assigning types to expressive Discourse Representation Structure (DRS) meaning representations. In terms of linguistic analysis, our typing methodology couples together the representation of phenomena at the same level of analysis that was traditionally considered to belong to distinctive layers. In the thesis, we claim that the realisation of sub-...

This paper presents Audioplethysmography (APG), a novel cardiac monitoring modality for active noise cancellation (ANC) headphones. APG sends a low intensity ultrasound probing signal using an ANC headphone's speakers and receives the echoes via the on-board feedback microphones. We observed that, as the volume of ear canals slightly changes with blood vessel deformations, the heartbeats will...