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...
BACKGROUND: This study aims to examine the worldwide prevalence of post-coronavirus disease 2019 (COVID-19) condition, through a systematic review and meta-analysis. Fatigue was the most common sympto...
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...
Importance: Depression is the leading cause of mental health-related disease burden and may be reduced by physical activity, but the dose-response relationship between activity and depression is uncer...
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...
BACKGROUND: Neoadjuvant or adjuvant chemotherapy confers a modest benefit over surgery alone for resectable non-small-cell lung cancer (NSCLC). The addition of nivolumab to neoadjuvant chemotherapy di...
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...
BACKGROUND: According to the Global Burden of Disease (GBD) study, headache disorders are among the most prevalent and disabling conditions worldwide. These variations render uncertain both the increa...
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...
The increasing global industrialization and over-exploitation of fossil fuels has induced the release of greenhouse gases, leading to an increase in global temperature and causing environmental issues...
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...
Qualitative research relies on nuanced judgements that require researcher reflexivity, yet reflexivity is often addressed superficially or overlooked completely during the research process. With the g...
High-entropy nanoparticles have become a rapidly growing area of research in recent years. However, this strong potential is also accompanied by grand challenges originating from their vast compositio...
Maintaining blood-brain barrier (BBB) integrity is crucial for the homeostasis of the central nervous system. Due to the dual role of inflammation in the progression of ischemic damage, more research...
This research explores Ferroptosis at the intersection of lipid metabolism and cell..., contributing new insights to the field of Engineering & Technology.
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.