Academic Articles & Research Papers

Development of a BIM-based AI-driven matching tool for LCA datasets

Abstract The construction sector significantly contributes to environmental issues and often relies on Life Cycle Assessment (LCA) for the quantification and optimization of its environmental impacts. One of the most time- and labour-intens...

Occupational exposures, complementarity and the potential consequences of A.I. for the labour market: some evidence from Ireland

Abstract The adoption of AI technology by industry could significantly disrupt our current understanding of “typical” economic activity. As AI comes to pervade more sectors and occupations over time, it is likely that this technology will g...

Normalized risk-based evaluation of machine learning-based classification models: A multiclass approach with applications in medical devices.

Artificial intelligence tools in dermatology education: A scoping review on their application, efficacy, and limitations

Introduction: Artificial Intelligence (AI) is increasingly explored for medical education, and dermatology, with its visual diagnostic focus, holds promise for AI-enhanced learning. However, evidence on its educational effectiveness remains...

Preparation and In Vitro Evaluation of the DOX@Mem-HMnO2 Bioinspired Nanosystem: A Proof-of-Concept Study.

APRICOIN: An Adaptive Approach for Prioritizing High-Risk Containers Inspections

Risk evaluation of the containers remains a difficult task, often due to incomplete or ambiguous information on containers. In addition, the evaluation process needs to be adapted on an ongoing basis to cope with emerging risk factors. Furt...

Enhancing Explainable Artificial Intelligence: Using Adaptive Feature Weight Genetic Explanation (AFWGE) with Pearson Correlation to Identify Crucial Feature Groups

The ‘black box’ nature of machine learning (ML) approaches makes it challenging to understand how most artificial intelligence (AI) models make decisions. Explainable AI (XAI) aims to provide analytical techniques to understand the behavior...

Women’s perceptions and attitudes towards the use of AI in mammography in Sweden: a qualitative interview study

Background Understanding women’s perspectives can help to create an effective and acceptable artificial intelligence (AI) implementation for triaging mammograms, ensuring a high proportion of screening-detected cancer. This study aimed to e...

A physics-informed spatiotemporal graph neural network for photovoltaic power forecasting and micro-anomaly localization

Accurate power forecasting and precise fault diagnosis are critical for the reliable operation of large-scale photovoltaic systems. However, existing data-driven models often fail to capture complex spatiotemporal dependencies and lack phys...

PET imaging enables direct evaluation of ferroptosis in HCC synergistically induced by anti-PD-L1 and Olaparib.

An Instructional Optimization Method Based on Bidirectional Transformer and Reinforcement Learning

With the rapid development of information technology, personalized education has become a key direction for improving the quality of online learning and optimizing individualized learning paths. However, accurately recommending appropriate ...

Towards an AI-Based Tailored Training Planning for Road Cyclists: A Case Study

In a world where the data is a central piece, we provide a novel technique to design training plans for road cyclists. This study exposes an in-depth review of a virtual coach based on state-of-the-art artificial intelligence techniques to ...

<bold>CroSSHeteroFL</bold>: Cross-Stratified Sampling Composition-Fitting to Federated Learning for Heterogeneous Clients

In the large-scale deployment of federated learning (FL) systems, the heterogeneity of clients, such as mobile phones and Internet of Things (IoT) devices with different configurations, constitutes a significant problem regarding fairness, ...

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...

AI enhanced diagnostic accuracy and workload reduction in hepatocellular carcinoma screening

Abstract Hepatocellular carcinoma (HCC) ultrasound screening encounters challenges related to accuracy and the workload of radiologists. This retrospective, multicenter study assessed four artificial intelligence (AI) enhanced strategies us...

Prospective evaluation of indocyanine green fluorescence for anastomotic site selection in laparoscopic colorectal cancer surgery.

Integrating PET/CT and correlative biomarkers for prospective evaluation of extramedullary disease in relapsed/refractory B-ALL: implications for CAR T-cell therapy.

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...

Accuracy and reliability of Manus, ChatGPT, and Claude in case-based dental diagnosis

IntroductionArtificial intelligence (AI), particularly large language models (LLMs), is transforming healthcare education and clinical decision-making. While models like ChatGPT and Claude have demonstrated utility in medical contexts, thei...