Explore the latest peer-reviewed research with AI-generated summaries, key findings, and insights for easy understanding. All content is legally sourced from academic metadata with links to original papers.
Abstract Modeling the effect of sequence variation on function is a fundamental problem for understanding and designing proteins. The conventional setting is limited, since a new model must be trained...
This research explores International Classification of Retinopathy of Prematurity,..., contributing new insights to the field of Artificial Intelligence.
Computational biology and bioinformatics provide vast data gold-mines from protein sequences, ideal for Language Models (LMs) taken from Natural Language Processing (NLP). Taken together, the results...
Hyperspectral (HS) images are characterized by approximately contiguous spectral information, enabling the fine identification of materials by capturing subtle spectral discrepancies. We evaluate the...
Machine learning models are poised to make a transformative impact on chemical sciences by dramatically accelerating computational algorithms and amplifying insights available from computational chemi...
This research explores Image fusion meets deep learning: A survey and perspective, contributing new insights to the field of Artificial Intelligence.
Federated learning (FL) is a distributed machine learning strategy that generates a global model by learning from multiple decentralized edge clients. We highlight an overview of FL and provide a comp...
Regression analysis makes up a large part of supervised machine learning, and consists of the prediction of a continuous independent target from a set of other predictor variables. Our results demonst...
This research explores default mode network in cognition: a topographical perspecti..., contributing new insights to the field of Artificial Intelligence.
Clinical annotations are one of the most popular resources available on the Pharmacogenomics Knowledgebase (PharmGKB). Overall, the system increases transparency, consistency, and reproducibility in L...
In this article, we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting di...
Abstract This paper reviews the current state of the art in artificial intelligence (AI) technologies and applications in the context of the creative industries. The potential of AI (or its developers...
INTRODUCTION: The Transparent Reporting of a multivariable prediction model of Individual Prognosis Or Diagnosis (TRIPOD) statement and the Prediction model Risk Of Bias ASsessment Tool (PROBAST) were...
This research explores Tomato plant disease detection using transfer learning with..., contributing new insights to the field of Artificial Intelligence.
Change detection (CD) aims to identify surface changes from bitemporal images. Experiments are conducted on both the CDD and the SYSU-CD dataset.
Extending the forecasting time is a critical demand for real applications,\nsuch as extreme weather early warning and long-term energy consumption\nplanning. In long-term\nforecasting, Autoformer yiel...
We observe that despite their hierarchical convolutional nature, the synthesis process of typical generative adversarial networks depends on absolute pixel coordinates in an unhealthy manner. The resu...
How can neural networks learn the rich internal representations required for difficult tasks such as recognizing objects or understanding language?
Research in artificial intelligence for radiology and radiotherapy has recently become increasingly reliant on the use of deep learning-based algorithms. Articles were categorised into basic, deformab...
This innovative approach to teaching the finite element method blends theoretical, textbook-based learning with practical application using online and video resources. Suitable for senior undergraduat...