12 papers · ranked by Valyu relevance
Alok Sharma, Artem Lysenko, Shangru Jia, Keith A. Boroevich + 1 more
The field of omics, driven by advances in high-throughput sequencing, faces a data explosion. This abundance of data offers unprecedented opportunities for predictive modeling in precision medicine, but also presents formidable challenges in data analysis and interpretation. Traditional machine learning (ML) techniques…
Alok Sharma, Yosvany López, Shangru Jia, Artem Lysenko + 2 more
'Keith A. Boroevich' 'Tatsuhiko Tsunoda'] Tabular data analysis is a critical task in various domains, enabling us to uncover valuable insights from structured datasets. While traditional machine learning methods can be used for feature engineering and dimensionality reduction, they often struggle to capture the…
Tansel Ersavas, Martin A. Smith, John S. Mattick
Convolutional Neural Networks (CNNs) have been central to the Deep Learning revolution and played a key role in initiating the new age of Artificial Intelligence. However, in recent years newer architectures such as Transformers have dominated both research and practical applications. While CNNs still play critical…
Elif İlgazi Kılıç, Şafak Kılıç
Background Cervical cancer remains one of the leading causes of gynecological mortality worldwide, largely due to the limitations of manual cytological screening, which is time-consuming and susceptible to inter-observer variability. Although deep learning has demonstrated strong potential for automating cervical…
Jeseok Lee, Byungwon Kim, Hongchuan Yu
Through the Human Microbiome Project, research on human-associated microbiomes has been conducted in various fields. New sequencing techniques such as Next Generation Sequencing (NGS) and High-Throughput Sequencing (HTS) have enabled the inclusion of a wide range of features of the microbiome. These advancements have…
Jason T. Smith, Marien Ochoa, Denzel Faulkner, Grant Haskins + 1 more
'Xavier Intes'] Title: Abstract. Significance Biomedical optics system design, image formation, and image analysis have primarily been guided by classical physical modeling and signal processing methodologies. Recently, however, deep learning (DL) has become a major paradigm in computational modeling and has…
Hazem M. Kotb, Tarek Gaber, Salem AlJanah, Hossam M. Zawbaa + 1 more
'Mohammed Alkhathami'] Insider threats pose a significant challenge to IT security, particularly with the rise of generative AI technologies, which can create convincing fake user profiles and mimic legitimate behaviors. Traditional intrusion detection systems struggle to differentiate between real and AI-generated…
Malik YOUSEF, Jens ALLMER
Deep learning is a powerful machine learning technique that can learn from large amounts of data using multiple layers of artificial neural networks. This paper reviews some applications of deep learning in bioinformatics, a field that deals with analyzing and interpreting biological data. We first introduce the basic…
HOSSEIN MORADIMOKHLES, GWO-JEN HWANG, HOSSEIN ZANGENEH, MARYAM POURJAMSHIDI + 1 more
The term “deep learning” has incorrect interpretations in education and technology disciplines. It describes a method of learning in which the objective is to achieve an in-depth understanding of topic rather than succumb to surface learning. "Non-surface learning" is undeniably related to deep information…
Sakib Mostafa, Debajyoti Mondal, Karim Panjvani, Leon Kochian + 1 more
'Ian Stavness'] The increasing human population and variable weather conditions, due to climate change, pose a threat to the world's food security. To improve global food security, we need to provide breeders with tools to develop crop cultivars that are more resilient to extreme weather conditions and provide growers…
Alexander Muacevic, John R Adler, Yash Garg, Karthik Seetharam + 3 more
'Manjari Sharma' 'Dipesh K Rohita' 'Waseem Nabi'] Computed tomography has played an instrumental role in the understanding of the pathophysiology of atherosclerosis in coronary artery disease. It enables visualization of the plaque obstruction and vessel stenosis in a comprehensive manner. As technology for computed…
Arnav Bhagwat, Soham Dutta, Debdeep Saha, Maddikara Jaya Bharata Reddy
'Maddikara Jaya Bharata Reddy'] With the advent of smart distribution grids, detection of defects in insulators with unmanned aerial vehicles as a part of distribution automation system (DAS) has attained a widespread attention. The defects are essential to detect to avoid damaging the service life of distribution…