Latest AI and machine learning research in work force for healthcare professionals.
The accelerated MRI reconstruction poses a challenging ill-posed inverse problem due to the significant undersampling in k-space. Deep neural networks, such as CNNs and ViTs, have shown substantial performance improvements for this task while encountering the dilemma between global receptive fields and efficient computation. To this end, this paper explores selective state space models (Mamba), ...
This research-in-progress paper presents a new project management framework that utilises GenAI technology. The framework is designed to address the common challenge of uniform team compositions in academic and research project teams, particularly in universities and research institutions. It does so by integrating sociologically identified patterns of successful team member personalities and ro...
Accurate human posture classification in images and videos is crucial for automated applications across various fields, including work safety, physi...
The widespread adoption of facial recognition (FR) models raises serious concerns about their potential misuse, motivating the development of anti-f...
Existing methods for code generation use code snippets as seed data, restricting the complexity and diversity of the synthesized data. In this paper...
In this work, we build upon the offline reinforcement learning algorithm TD7, which incorporates State-Action Learned Embeddings (SALE) and a priori...
The crisis of mental health issues is escalating. Effective counseling serves as a critical lifeline for individuals suffering from conditions like ...
Tongue diagnosis is a vital tool in Western and Traditional Chinese Medicine, providing key insights into a patient's health by analyzing tongue att...
Recent years have witnessed significant advancements in text-guided style transfer, primarily attributed to innovations in diffusion models. These m...
Large language models (LLMs) are increasingly attracting the attention of healthcare professionals for their potential to assist in diagnostic asses...
Disease name normalization is an important task in the medical domain. It classifies disease names written in various formats into standardized name...
Accurate prediction of the temporal dynamics of biological systems is crucial for informing timely and effective interventions, e.g., in ecological or...
Compiling and characterising the diversity of bacterial pathogens of humans is a critical challenge to tackle infection risk, especially in the contex...
Functional RNAs perform diverse catalytic roles, yet natural sequences represent only a narrow subset of what is possible. Rediscovering such activiti...
Diversity exists throughout biology, playing an important role in maintaining robustness and stability. The same is true of the brain, as has become i...
In pathology, reconstructing adjacent tissue parts enables an overview of the macro environment of objects like tumors. Especially, malignoma are of i...
Bacteria use antagonistic interbacterial weapons such as polymorphic toxin secretion systems (TSS) to compete for niches in the human gut microbiome. ...
Given the well-established structural and functional changes in the aging brain, it is widely assumed that cognitive aging is primarily driven by robu...
Pathogenic KCNQ2 variants are associated with developmental and epileptic encephalopathy (KCNQ2-DEE), a devastating disorder characterized by neonatal...
Recognition of protospacer adjacent motifs (PAMs) is crucial for target site recognition by CRISPR–Cas systems. In genome editing applications, the re...