Academic Articles & Research Papers

Prevalence and non-invasive predictive models of vitamin D insufficiency in Paraguayan youth: the role of body composition and traditional mate consumption.

Comparison of predictive models for estimating scorpion, snake, and spider envenomation under warming scenarios in São Paulo State, Brazil.

Predicting land use and land cover changes for sustainable land management using CA-Markov modelling and GIS techniques

Abstract This study addresses the significant issue of rapid land use and land cover (LULC) changes in Lahore District, which is critical for supporting ecological management and sustainable land-use planning. Understanding these changes is...

AI for identifying social norm violation

Abstract Identifying social norms and their violation is a challenge facing several projects in computational science. This paper presents a novel approach to identifying social norm violations. We used GPT-3, zero-shot classification, and ...

Effect of fire-source location on flame behavior and temperature distribution in subway carriages with multiple lateral openings

Urban rail transit has been widely adopted to alleviate surface traffic congestion. However, subway fire safety remains a critical concern because of the confined carriage space, high occupant density, and complex ventilation conditions. Mo...

Effect of chemical treatment on the mechanical and thermal performance of flax fiber reinforced aluminium 6082 laminate: a machine learning-enhanced investigation

Abstract This work examined the role of alkaline and epoxy-based surface chemical treatments on the mechanical and thermal properties of flax fiber reinforced Aluminum Alloy 6082 hybrid Fiber Metal Laminates (FMLs), integrated with machine ...

Optimization Strategies in Quantum Machine Learning: A Performance Analysis

This study presents a comprehensive comparison of multiple optimization algorithms applied to a quantum classification model, utilizing the Cleveland dataset. Specifically, the research focuses on three prominent optimizers—COBYLA, L-BFGS-B...

Tumor probability mapping of fluorescence intensity during image-guided surgery of head and neck cancer

Abstract Achieving negative surgical margins remains a critical determinant of local recurrence and survival in head and neck cancer (HNC) surgery. Current intraoperative margin assessment techniques, including frozen section analysis, suff...

Developing Clinical Risk Prediction Models for Worsening Heart Failure Events and Death by Left Ventricular Ejection Fraction

Background There is a need to develop electronic health record–based predictive models for worsening heart failure (WHF) events across clinical settings and across the spectrum of left ventricular ejection fraction (LVEF). Methods and Resul...

Explainable hybrid deep learning framework for air quality index prediction in Indian cities

Abstract Air pollution constitutes one of the most pressing environmental and public health crises of the twenty-first century, disproportionately affecting rapidly urbanising nations such as India. Accurate prediction of the Air Quality In...

Scalable and accurate deep learning with electronic health records

Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variabl...

A machine learning and clustering-based approach for county-level COVID-19 analysis.

COVID-19 is a global pandemic threatening the lives and livelihood of millions of people across the world. Due to its novelty and quick spread, scientists have had difficulty in creating accurate forecasts for this disease. In part, this is...

Improving Intrusion Detection Model Prediction by Threshold Adaptation

Network traffic exhibits a high level of variability over short periods of time. This variability impacts negatively on the accuracy of anomaly-based network intrusion detection systems (IDS) that are built using predictive models in a batc...

Portable NIR Spectroscopy Combined with Machine Learning for Kiwi Ripeness Classification: An Approach to Precision Farming

This study aims to evaluate and classify the ripening stages of yellow-fleshed kiwifruit by integrating spectral and physicochemical data collected from the pre-harvest phase through 60 days of storage. A portable near-infrared (NIR) spectr...

When more is not always better: exercise dose and children’s cognitive development from an interpretable machine learning perspective

BackgroundExercise intervention has been associated with cognitive development in children. However, current study methods have not clarified the potential nonlinear association between exercise dosage and cognitive ability, and interpretab...

Machine learning-based diagnostic prediction of minimal change disease: model development study

Abstract Minimal change disease (MCD) is a common cause of nephrotic syndrome. Due to its rapid progression, early detection is essential; however, definitive diagnosis requires invasive kidney biopsy. This study aims to develop non-invasiv...

Artificial intelligence in orthopaedic surgery

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need ...

AI-Driven Identification of Critical Dependencies in US-China Technology Supply Chains: Implications for Economic Security Policy

This research examines the critical dependencies within US-China technology supply chains through advanced artificial intelligence methodologies, addressing significant economic security implications in an era of strategic competition. The ...