AIMC Topic: Humans

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Multi-dimensional interpretable deep learning-radiomics based on intra-tumoral and spatial habitat for preoperative prediction of thymic epithelial tumours risk categorisation.

Acta oncologica (Stockholm, Sweden)
BACKGROUND AND PURPOSE: This study aims to develop and compare combined models based on enhanced CT-based radiomics, multi-dimensional deep learning, clinical-conventional imaging and spatial habitat analysis to achieve accurate prediction of thymoma...

Exploring the repository of de novo-designed bifunctional antimicrobial peptides through deep learning.

eLife
Antimicrobial peptides (AMPs) are attractive candidates to combat antibiotic resistance for their capability to target biomembranes and restrict a wide range of pathogens. It is a daunting challenge to discover novel AMPs due to their sparse distribu...

Control of medical digital twins with artificial neural networks.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
The objective of precision medicine is to tailor interventions to an individual patient's unique characteristics. A key technology for this purpose involves medical digital twins, computational models of human biology that can be personalized and dyn...

Prediction of peripheral lymph node metastasis (LNM) in thyroid cancer using delta radiomics derived from enhanced CT combined with multiple machine learning algorithms.

European journal of medical research
OBJECTIVES: This study aimed to develop a model for predicting peripheral lymph node metastasis (LNM) in thyroid cancer patients by combining enhanced CT radiomic features with machine learning algorithms. It increased the clinical utility and interp...

Enhancing parkinson disease detection through feature based deep learning with autoencoders and neural networks.

Scientific reports
Parkinson's disease is a neurodegenerative disorder that is associated with aging, leading to the progressive deterioration of certain regions of the brain. Accurate and timely diagnosis plays a crucial role in facilitating optimal therapy and improv...

Exploring the application of deep learning methods for polygenic risk score estimation.

Biomedical physics & engineering express
. Polygenic risk scores (PRS) summarise genetic information into a single number with clinical and research uses. Deep learning (DL) has revolutionised multiple fields, however, the impact of DL on PRSs has been less significant. We explore how DL ca...

Redefining pedagogy with artificial intelligence: How nursing students are shaping the future of learning.

Nurse education in practice
AIM: This study aimed to explore the factors influencing undergraduate nursing students' use of artificial intelligence (AI) tools in their studies, examining how this usage shapes their learning experiences and perceptions of traditional pedagogical...

Deep learning and robotics enabled approach for audio based emotional pragmatics deficits identification in social communication disorders.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
The aim of this study is to develop Deep Learning (DL) enabled robotic systems to identify audio-based emotional pragmatics deficits in individuals with social pragmatic communication deficits. The novelty of the work stems from its integration of de...

Metabolomics and machine learning approaches for diagnostic biomarkers screening in systemic light chain amyloidosis.

Annals of hematology
Delayed diagnosis of systemic light chain (AL) amyloidosis is common and associated with worse survival and early mortality. Current diagnosis still relies on invasive tissue biopsies, highlighting the need for sensitive, noninvasive biomarkers for e...

Sparse connectivity enables efficient information processing in cortex-like artificial neural networks.

Frontiers in neural circuits
Neurons in cortical networks are very sparsely connected; even neurons whose axons and dendrites overlap are highly unlikely to form a synaptic connection. What is the relevance of such sparse connectivity for a network's function? Surprisingly, it h...