Data Augmentation Application in Deep Learning Drug Discovery by Utilizing Relationships Between Biological and Medical Entities

APPLICATION OF MACHINE LEARNING FOR MASS CYTOMETRY DATA ANALYSIS OF CHRONIC LYMPHOCYTIC LEUKAEMIA

Muizdeen Raji

Mass cytometry is a powerful technique for quantifying intracellular and membrane proteins at single-cell resolution. However, the vast amount of data it generates requires advanced analytical methods to extract meaningful biological insights. While machine learning (ML) has emer…Read more

Also available via: Open MIND

Unsupervised Deep-learning Methods for Low-dose Computed Tomography Reconstruction

Ran An

Computed tomography (CT) has become an indispensable imaging technique in medical diagnostics and industrial applications, owing to its non-invasive nature and high resolution in visualizing object internal structures. While X-ray CT (X-ray computed tomography) significantly enha…Read more

Also available via: Open MIND

Essays on Financial Machine Learning: Nonlinearity, Predictability and Data-Theory Integration

Yinuo Wang

Also available via: Open MIND

Combating Data and Target Shifts in Visual Tasks

Zhaorui Tan

The rapid advancement of deep learning models for visual tasks has led to significant progress in many domains. However, a key challenge remains: ensuring that models can generalize effectively to unseen samples or novel classes, especially in real-world scenarios where training…Read more

Also available via: Open MIND

A UAV-Based Framework for Community-Scale Residential Building Energy Modelling in China

Mengfan Jin

With increasing emphasis on energy efficiency and carbon emission reduction in the building sector, rapid and scalable energy modelling of existing buildings is critical for retrofit projects and policy development. Conventional surveys, data collection and energy modelling proce…Read more

Also available via: Open MIND

Utilizing Concept Ontologies for Designing Neural Network-Based Classifiers

Kamil Szwed

Deep neural networks have achieved substantial success in image, text, and signal analysis, but their advantage is less consistent for heterogeneous tabular data, where tree-based ensemble methods often remain strong baselines. This study proposes CANON (Cross-Attention Neuro-sym…Read more