Sort by
Refine Your Search
-
this context, emerging cryobioprinting technologies present a transformative approach for creating complex, cell‐laden constructs capable of mimicking the architecture and functionality of native tissues
-
of the bioprinting process. Objective 2: Training of a deep learning model to predict inputs that will achieve bioprinted scaffolds with the required print fidelity and scaffold micro-architecture. Objective 3
-
are revolutionising the field of tissue engineering and regenerative medicine by enabling precise spatial control over the composition, architecture, and bioactivity of printed constructs. Within this transformative
-
evaluating CRN ML models 3. Designing and developing CRN ML architectures for tasks of chemical interest, including reaction property prediction and reaction link prediction. 4. Predicting the properties and