Preliminary development of anatomically realistic breast tumor models for microwave imaging

Pelicano, Ana Catarina; Araújo, Nuno A. M.; Conceição, Raquel C.

doi:10.23919/eucap53622.2022.9769591

Cited by 2 publications

(1 citation statement)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results show the promising contribution of ML in the detection of breast cancer. Peli et al 125 classify tumors in magnetic resonance images as malignant or benign based on their morphological features; a preliminary investigation was conducted using three classifiers where KNN outperforms with the accuracy of 85% than linear discriminant analysis (LDA) and support vector machine (SVM).…”

Section: State-of-art Techniques Of Ai-assisted Mwi In Disease Diagnosismentioning

confidence: 99%

Emerging paradigms in microwave imaging technology for biomedical applications: unleashing the power of artificial intelligence

Khalid,

Zubair,

Mehmood

et al. 2024

npj Imaging

View full text Add to dashboard Cite

In recent years, microwave imaging (MWI) has emerged as a non-ionizing and cost-effective modality in healthcare, specifically within medical imaging. Concurrently, advances in artificial intelligence (AI) have significantly augmented the capabilities of medical imaging tools. This paper explores the intersection of these two domains, focusing on the integration of AI algorithms into MWI techniques to elevate accuracy and overall performance. Within the scope of existing literature, representative prior works are compared concerning the application of AI in both the “MWI for Healthcare Applications" and “Artificial Intelligence Assistance In MWI" sections. This comparative analysis sheds light on the diverse approaches employed to enhance the synergy between AI and MWI. While highlighting the state-of-the-art technology in MWI and its historical context, this paper delves into the historical taxonomy of AI-assisted MWI, elucidating the evolution of intelligent systems within this domain. Moreover, it critically examines prominent works, providing a nuanced understanding of the advancements and challenges encountered. Addressing the limitations and challenges inherent in developing AI-assisted MWI systems like Generalization to different conditions, Generalization to different conditions, etc the paper offers a brief synopsis of these obstacles, emphasizing the importance of overcoming them for robust and reliable results in actual clinical environments. Finally, the paper not only underscores the current advancements but also anticipates future innovations and developments in utilizing AI for MWI applications in healthcare.

show abstract

Section: State-of-art Techniques Of Ai-assisted Mwi In Disease Diagnosismentioning

confidence: 99%

Emerging paradigms in microwave imaging technology for biomedical applications: unleashing the power of artificial intelligence

Khalid,

Zubair,

Mehmood

et al. 2024

npj Imaging

View full text Add to dashboard Cite

show abstract

Can the text features of regulatory inquiry letters predict companies’ financial restatements? Evidence from China

Zhang,

Cao,

et al. 2024

View full text Add to dashboard Cite

PurposeSince the implementation of the regulatory inquiry system, research on its impact on information disclosure in the capital market has been increasing. This article focuses on a specific area of study using Chinese annual report inquiry letters as the basis. From a text mining perspective, we explore whether the textual information contained in these inquiry letters can help predict financial restatement behavior of the inquired companies.Design/methodology/approachPython was used to process the data, nonparametric tests were conducted for hypothesis testing and indicator selection, and six machine learning models were employed to predict financial restatements.FindingsSome text feature indicators in the models that exhibit significant differences are useful for predicting financial restatements, particularly the proportion of formal positive words and stopwords, readability, total word count and certain textual topics. Securities regulatory authorities are increasingly focusing on the accounting and financial aspects of companies' annual reports.Research limitations/implicationsThis study explores the textual information in annual report inquiry letters, which can provide insights for other scholars into research methods and content. Besides, it can assist with decision making for participants in the capital market.Originality/valueWe use information technology to study the textual information in annual report inquiry letters and apply it to forecast financial restatements, which enriches the research in the field of regulatory inquiries.

show abstract

Preliminary development of anatomically realistic breast tumor models for microwave imaging

Cited by 2 publications

References 17 publications

Emerging paradigms in microwave imaging technology for biomedical applications: unleashing the power of artificial intelligence

Emerging paradigms in microwave imaging technology for biomedical applications: unleashing the power of artificial intelligence

Can the text features of regulatory inquiry letters predict companies’ financial restatements? Evidence from China

Contact Info

Product

Resources

About