Academic Articles & Research Papers

Taxonomy-based data representation for data mining: an example of the magnitude of risk associated with H. pylori infection

Abstract Background The amount of available and potentially significant data describing study subjects is ever growing with the introduction and integration of different registries and data banks. The single specific attribute of these data...

Identification of arachidonic acid metabolism-related diagnostic markers in heart failure based on bioinformatics analysis and machine learning

BackgroundHeart failure (HF) represents the terminal phase of multiple cardiovascular conditions and is associated with significant morbidity and mortality rates. Arachidonic acid (AA), an essential fatty acid, plays a crucial role in modul...

Machine Learning Inversion of Runway Base-Course Parameters Using Multi-Domain Vibration Features Under Moving Aircraft Loads

Accurate identification of runway base-course parameters is an important basis for structural condition assessment, yet separating base-course elastic modulus, thickness, and local damage from runway responses under moving aircraft loads re...

Evaluating Model Resilience to Data Poisoning Attacks: A Comparative Study

Machine learning (ML) has become a cornerstone of critical applications, but its vulnerability to data poisoning attacks threatens system reliability and trustworthiness. Prior studies have begun to investigate the impact of data poisoning ...

Introduction to Machine Learning

The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity ...

Evaluation of the Applications of using Global free Digital Elevation Models and GNSS-RTK data for Agricultural purposes in Egypt using Machine Learning

Agriculture is a vital component of Egypt's economy; therefore, using Digital Elevation Models (DEMs) in agricultural planning in Egypt has significant benefits regarding water management, site appropriateness assessment, flood risk mitigat...

The voice of depression: speech features as biomarkers for major depressive disorder

Abstract Background Psychiatry faces a challenge due to the lack of objective biomarkers, as current assessments are based on subjective evaluations. Automated speech analysis shows promise in detecting symptom severity in depressed patient...

A feature selection and scoring scheme for dimensionality reduction in a machine learning task

Selection of important features is very vital in machine learning tasks involving high-dimensional dataset with large features. It helps in reducing the dimensionality of a dataset and improving model performance. Most of the feature select...

Resistance to Medical Artificial Intelligence

Abstract Artificial intelligence (AI) is revolutionizing healthcare, but little is known about consumer receptivity to AI in medicine. Consumers are reluctant to utilize healthcare provided by AI in real and hypothetical choices, separate a...

Representations and Benchmarking of Modern Visual SLAM Systems

Simultaneous Localisation And Mapping (SLAM) has long been recognised as a core problem to be solved within countless emerging mobile applications that require intelligent interaction or navigation in an environment. Classical solutions to ...

Energy-Efficient Dynamic RTO with Enhanced Stability for CoAP-Based IoT Networks

The Constrained Application Protocol (CoAP) is widely adopted to ensure end-to-end reliability in resource-constrained Artificial Intelligence of Things (AIoT) and Wireless Sensor Networks (WSNs). However, CoAP’s default retransmission time...

CeCILE - An Artificial Intelligence Based Cell-Detection for the Evaluation of Radiation Effects in Eucaryotic Cells

The fundamental basis in the development of novel radiotherapy methods is in-vitro cellular studies. To assess different endpoints of cellular reactions to irradiation like proliferation, cell cycle arrest, and cell death, several assays ar...

Ranking-Based Case Retrieval with Graph Neural Networks in Process-Oriented Case-Based Reasoning

In Process-Oriented Case-Based Reasoning (POCBR), experiential knowledge from previous problem-solving situations is retrieved from a case base to be reused for upcoming problems. The task of retrieval is approached in previous work by usin...

Advances in ligand-targeted nanodelivery systems for leukemia therapy: from single- to dual-ligand strategies

Abstract Background Leukemia is a highly heterogeneous and aggressive hematological malignancy. Current therapeutic approaches (e.g. chemotherapy, radiotherapy, small-molecule targeted therapies, and hematopoietic stem cell transplantation,...

Evaluation of the clinical course of immune-mediated polyneuropathy in cats after treatment with human intravenous immunoglobulins.

Evaluation of Alysis-001 cuffless blood pressure estimation algorithm against the European Society of Hypertension awake/asleep test criteria in hypertensive patients.

Economic Evaluations of Artificial Intelligence Implementation in Diabetic Retinopathy Screening

Diabetic retinopathy (DR) is a common complication of diabetes that damages retinal blood vessels and can lead to vision impairment. The application of Artificial Intelligence (AI) in DR screening offers a promising alternative to conventio...

Evaluating new technology for biodiversity monitoring: Are drone surveys biased?

Abstract Drones and machine learning‐based automated detection methods are being used by ecologists to conduct wildlife surveys with increasing frequency. When traditional survey methods have been evaluated, a range of factors have been fou...

Expert Agents for Social and Emotional Learning: An Agentic Graph Retrieval Augmented Generation Approach

The positive impact of Social and Emotional Learning (SEL) activities in schools is widely recognized in various sectors, including mental health, social relationships, and academic performance of students. This impact can be efficiently re...

Adaptive habitat biogeography-based optimizer for optimizing deep CNN hyperparameters in image classification

Deep Convolutional Neural Networks (DCNNs) have shown remarkable success in image classification tasks, but optimizing their hyperparameters can be challenging due to their complex structure. This paper develops the Adaptive Habitat Biogeog...