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.
Disease risk prediction is a rising challenge in the medical domain. Finally, this paper summarises which KNN variant is the most promising candidate to follow under the consideration of three perform...
Contrastive models like CLIP have been shown to learn robust representations of images that capture both semantics and style. Moreover, the joint embedding space of CLIP enables language-guided image...
BACKGROUND: Transfer learning (TL) with convolutional neural networks aims to improve performances on a new task by leveraging the knowledge of similar tasks learned in advance. We encourage data scie...
Modern deep learning methods constitute incredibly powerful tools to tackle a myriad of challenging problems. This tutorial provides deep learning practitioners with an overview of the relevant litera...
Network approaches to psychometric constructs, in which constructs are modeled in terms of interactions between their constituent factors, have rapidly gained popularity in psychology. Possible extens...
Abstract Transmembrane proteins span the lipid bilayer and are divided into two major structural classes, namely alpha helical and beta barrels. We introduce DeepTMHMM, a deep learning protein languag...
Clinicians and software developers need to understand how proposed machine learning (ML) models could improve patient care. This paper looks at previous ML studies done in gastroenterology, provides a...
The Earth system model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are compara...
Large language models have been shown to achieve remarkable performance across a variety of natural language tasks using few-shot learning, which drastically reduces the number of task-specific traini...
Abstract Deep learning (DL) is one of the fastest-growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based, spectral, and textual data modalities. F...
This research explores Recent advances and clinical applications of deep learning i..., contributing new insights to the field of Artificial Intelligence.
Abstract It is common to split a dataset into training and testing sets before fitting a statistical or machine learning model. However, there is no clear guidance on how much data should be used for...
This review paper provides an overview of data pre-processing in Machine learning, focusing on all types of problems while building the machine learning problems. To decrease the dependency on trainin...
The desire to understand how the brain generates and patterns behavior has driven rapid methodological innovation in tools to quantify natural animal behavior. SLEAP achieves greater accuracy and spee...
Transformer with self-attention has led to the revolutionizing of natural language processing field, and recently inspires the emergence of Transformer-style architecture design with competitive resul...
Recent advances in spatially resolved transcriptomics have enabled comprehensive measurements of gene expression patterns while retaining the spatial context of the tissue microenvironment. STAGATE co...
Inductive content analysis (ICA), or qualitative content analysis, is a method of qualitative data analysis well-suited to use in health-related research, particularly in relatively small-scale, non-c...
This research explores PIAFusion: A progressive infrared and visible image fusion n..., contributing new insights to the field of Artificial Intelligence.
We investigate the optimal model size and number of tokens for training a transformer language model under a given compute budget. This also means that Chinchilla uses substantially less compute for f...
This research explores Human Action Recognition and Prediction: A Survey, contributing new insights to the field of Artificial Intelligence.