Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
RADAR-AD: assessment of multiple remote monitoring technologies for early detection of Alzheimer's disease.
Alzheimers Res Ther
January 2025
Fraunhofer Institute for Algorithms and Scientific Computing SCAI, Sankt Augustin, Germany.
Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting millions worldwide, leading to cognitive and functional decline. Early detection and intervention are crucial for enhancing the quality of life of patients and their families. Remote Monitoring Technologies (RMTs) offer a promising solution for early detection by tracking changes in behavioral and cognitive functions, such as memory, language, and problem-solving skills.
View Article and Find Full Text PDFFungal lignocellulolytic enzymes: an in silico and full factorial design approach.
World J Microbiol Biotechnol
January 2025
Graduate Program in Bioscience Technologies, Universidade Tecnológica Federal do Paraná, Toledo, Paraná, Brazil.
Efficient degradation of lignocellulosic biomass is key for the production of value-added products, contributing to sustainable and renewable solutions. This study employs a two-step approach to evaluate lignocellulolytic enzymes of Ceratocystis paradoxa, Colletotrichum falcatum, and Sporisorium scitamineum. First, an in silico genomic analysis was conducted to predict the potential enzyme groups produced by these fungi.
View Article and Find Full Text PDFImproved display and detection of small renal stones using photon-counting detector CT compared to conventional energy-integrating detector CT.
Abdom Radiol (NY)
January 2025
Mayo Clinic, Rochester, MN, USA.
Purpose: To compare same-day photon-counting detector CT (PCD-CT) to conventional energy-integrating detector CT (EID-CT) for detection of small renal stones (≤ 3 mm).
Methods: Patients undergoing clinical dual-energy EID-CT for known or suspected stone disease underwent same-day research PCD-CT. Patients with greater than 10 stones and no visible stones under 3 mm were excluded.
Capsule network approach for monkeypox (CAPSMON) detection and subclassification in medical imaging system.
Sci Rep
January 2025
Department of Computer Science and Engineering, E.G.S. Pillay Engineering College, Nagapattinam, 611002, Tamil Nadu, India.
In response to the pressing need for the detection of Monkeypox caused by the Monkeypox virus (MPXV), this study introduces the Enhanced Spatial-Awareness Capsule Network (ESACN), a Capsule Network architecture designed for the precise multi-class classification of dermatological images. Addressing the shortcomings of traditional Machine Learning and Deep Learning models, our ESACN model utilizes the dynamic routing and spatial hierarchy capabilities of CapsNets to differentiate complex patterns such as those seen in monkeypox, chickenpox, measles, and normal skin presentations. CapsNets' inherent ability to recognize and process crucial spatial relationships within images outperforms conventional CNNs, particularly in tasks that require the distinction of visually similar classes.
View Article and Find Full Text PDFDLCDroid an android apps analysis framework to analyse the dynamically loaded code.
Sci Rep
January 2025
Department of Computer Science and Engineering, Engineering College Ajmer, Ajmer, Rajasthan, India.
To combat dynamically loaded code in anti-emulated environments, DLCDroid is an Android app analysis framework. DL-CDroid uses the reflection API to effectively identify information leaks due to dynamically loaded code within malicious apps, incorporating static and dynamic analysis techniques. The Dynamically Loaded Code (DLC) technique employs Java features to allow Android apps to dynamically expand their functionality at runtime.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!