Briden, M. (CSE) – Representation Learning and Generative Forecasting for Noisy and Limited Clinical Data: Applications in Wound Healing and EEG
Engineering 2 Engineering 2 1156 High Street, Santa Cruz, CAThe rapid integration of artificial intelligence and machine learning into clinical practice has driven advances in disease classification, segmentation, and clinical decision support. However, the complexities of medical data pose a challenge to widespread adoption. The rarity of medical conditions, ethical considerations, and varying acquisition protocols leads to limited and noisy data. The time-intensive process […]