The development of novel biomaterials is a challenging process, complicated by a design
space with high dimensionality. Requirements for performance in the complex biological …

Combinational pharmacotherapy with the synergistic/additive effect is a powerful treatment
strategy for complex diseases such as malignancies. Identifying synergistic combinations …

Motivation: Accurate and efficient prediction of molecular properties is one of the
fundamental issues in drug design and discovery pipelines. Traditional feature engineering …

Clinical datasets are commonly limited in size, thus restraining applications of Machine
Learning (ML) techniques for predictive modelling in clinical research and organ …

Motivation Single-centre studies in medical domain are often characterised by limited
samples due to the complexity and high costs of patient data collection. Machine learning …

Technological advances in healthcare have saved innumerable patients and are
continuously improving our quality of life. Fatigue among health indicators of individuals has …

High-performance thermal interface materials (TIMs) have attracted persistent attention for
the design and development of miniaturized nanoelectronic devices; however, a large …

Automated cell classification is an important yet a challenging computer vision task with
significant benefits to biomedicine. In recent years, there have been several studies …

Experimental datasets in bioengineering are commonly limited in size, thus rendering
Machine Learning (ML) impractical for predictive modelling. Novel techniques of multiple …

In early stage biomedical studies, small datasets are common due to the high cost and
difficulty of sample collection with human subjects. This complicates the validation of …