Academic Articles & Research Papers

Unsupervised machine learning identifies distinct ALS molecular subtypes in post-mortem motor cortex and blood expression data

Abstract Amyotrophic lateral sclerosis (ALS) displays considerable clinical and genetic heterogeneity. Machine learning approaches have previously been utilised for patient stratification in ALS as they can disentangle complex disease lands...

IEEE Access Special Section Editorial: 5G and Beyond Mobile Wireless Communications Enabling Intelligent Mobility

Increasing urbanization is one major trend that shapes tomorrow’s society; by 2050, more than 85% of the developed world’s population will live in a comparatively small number of ever-growing cities. Within such cities ...

Radiomics and radiogenomics: extracting more information from medical images for the diagnosis and prognostic prediction of ovarian cancer

Abstract Ovarian cancer (OC) remains one of the most lethal gynecological malignancies globally. Despite the implementation of various medical imaging approaches for OC screening, achieving accurate differential diagnosis of ovarian tumors ...

Artificial intelligence: foundations of computational agents

Recent decades have witnessed the emergence of artificial intelligence as a serious science and engineering discipline. Artificial Intelligence: Foundations of Computational Agents is a textbook aimed at junior to senior undergraduate stude...

Expert system for managing data on the competencies of a modern manager

In the modern economy, digitalization has become one of the key components of the Russian Federation regions socio-economic development. Enterprises of various industries are faced with the need to process large amounts of data, which great...

A Machine Learning-Guided Lyric Analysis Peer Support Intervention (LAPSI) for Psychological Distress in South African Women: Protocol for an Exploratory Sequential Mixed Methods Study.

Risk factor assessments of temporomandibular disorders via machine learning

Abstract This study aimed to use artificial intelligence to determine whether biological and psychosocial factors, such as stress, socioeconomic status, and working conditions, were major risk factors for temporomandibular disorders (TMDs)....

Health Equity Journal: Special Issue Guest Editorial

The practices of contemporary clinical decision-making and care rely heavily on racial biological essentialism, which is a set of ideas originating in modern science that describes populations as comprising distinct subpopulations with uniq...

Cost-Effective Design, Content Management System Implementation and Artificial Intelligence Support of Greek Government AADE, myDATA Web Service for Generic Government Infrastructure, a Complete Analysis

One significant digital initiative that is changing Greece’s tax environment is the myDATA platform. The platform, which is a component of the wider digital governance agenda, provides significant added value to enterprises and the tax admi...

Artificial Intelligence for developing a personalised functional profile and supporting upper-limb rehabilitation decision-making in children with unilateral Cerebral Palsy (AInCP): protocol for an observational study.

Enabling Technologies and Recent Advancements of Smart Facility Management

With various emerging technologies and integration possibilities, smart facility management has gained wide interest in recent years. Several technologies were introduced to support facilities management and improve decision-making, such as...

Artificial Intelligence and Surgical Decision-making

Importance: Surgeons make complex, high-stakes decisions under time constraints and uncertainty, with significant effect on patient outcomes. This review describes the weaknesses of traditional clinical decision-support systems and proposes...

Global perspectives on MASCC clinical practice guidelines: awareness, implementation and insights to inform future updates.

Personalized ideological content recommendation via reinforcement learning as a digital therapeutic for anxiety reduction in youth

Abstract Adaptive digital therapies are needed with increasing rates of youth anxiety. However, existing systems lack personalization and dynamic learning. To solve this, the proposed research is to build a personalized ideological content ...

Paddy Yield Prediction in Tamilnadu Delta Region Using MLR-LSTM Model

Crop yield forecasting has been well studied in recent decades and is significant in protecting food security. Crop growth is a complex phenomenon that depends on various factors. Machine learning and deep learning trends have emerged as im...

Comparative architectural evaluation of CNN models with alternative classifiers for UAV-based detection of damaged green zones

Unmanned aerial vehicle imagery provides a practical and high-resolution data source for monitoring the spatial condition of urban and peri-urban green zones. However, the reliable detection of damaged, stressed, or declining vegetation are...

The co-curation of collective memory: artificial intelligence, Holocaust survivor testimony and the contribution of museum educators

Holocaust survivor testimony is increasingly being preserved using emerging technologies in preparation for a post-survivor era. A key approach to this process is exemplified by the Dimensions in Testimony platform developed by the Universi...

Imago Imaginis

Teaching formal analysis in art history often reveals gaps between students’ visual perception and their analytical articulation. This study explores the pedagogical potential of AI image generators in art history education, focusing on the...

Artificial Intelligence for Lentigo Maligna: Automated Margin Assessment via Sox-10-Based Melanocyte Density Mapping

Lentigo maligna (LM) is a melanoma in situ with high cumulative sun damage. Histological evaluation of resection margins is difficult and time-consuming. Melanocyte density (MD) is a suitable, quantifiable, and reproducible diagnostic crite...

On the practical aspects of machine learning based active power loss forecasting in transmission networks

Abstract The cost for covering active power losses makes a significant item in transmission system operators (TSO) annual budgets, and still it received limited attention in the existing literature. The focus of accurate power loss forecast...