This paper reviews the use of an intracavitary mold in the radiotherapeutic management of recurrent sub-orbital carcinoma of the maxillary sinus. An overview of the clinical features of antral carcinomas and the concept of brachytherapy in the management of these lesions is presented. Brachytherapy is usually reserved for relatively accessible lesions. Post-surgical and radiation-induced trismus can be a complicating factor, as in the case presented, where the inter-incisal distance was less than three millimeters. To circumvent the problem, a multi-layer antral plug was utilized as a carrier for the radioactive sources, and its construction is described.
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Neuroimage
January 2025
College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China; Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China. Electronic address:
Dynamic brain networks (DBNs) can capture the intricate connections and temporal evolution among brain regions, becoming increasingly crucial in the diagnosis of neurological disorders. However, most existing researches tend to focus on isolated brain network sequence segmented by sliding windows, and they are difficult to effectively uncover the higher-order spatio-temporal topological pattern in DBNs. Meantime, it remains a challenge to utilize the structure connectivity prior in the DBNs analysis.
View Article and Find Full Text PDFBMC Oral Health
January 2025
Department of Clinical Dentistry, Faculty of Medicine, University of Bergen, Bergen, Norway.
Background: In the last years, artificial intelligence (AI) has contributed to improving healthcare including dentistry. The objective of this study was to develop a machine learning (ML) model for early childhood caries (ECC) prediction by identifying crucial health behaviours within mother-child pairs.
Methods: For the analysis, we utilized a representative sample of 724 mothers with children under six years in Bangladesh.
Biomedicine (Taipei)
December 2024
Bioinformatics Department, Genetic Engineering and Biotechnology Research Institute, University of Sadat City, Sadat City, Egypt.
Background: One of the most challenging cancers is triple-negative breast cancer, which is subdivided into many molecular subtypes. Due to the high degree of heterogeneity, the role of precision medicine remains challenging. With the use of machine learning (ML)-guided gene selection, the differential gene expression analysis can be optimized, and eventually, the process of precision medicine can see great advancement through biomarker discovery.
View Article and Find Full Text PDFPLoS One
January 2025
Geosciences Department, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, KSA.
Estimating seismic anisotropy parameters, such as Thomson's parameters, is crucial for investigating fractured and finely layered geological media. However, many inversion methods rely on complex physical models with initial assumptions, leading to non-reproducible estimates and subjective fracture interpretation. To address these limitations, this study utilizes machine learning methods: support vector regression, extreme gradient boost, multi-layer perceptron, and a convolutional neural network.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China.
Electrocardiogram (ECG) signals contain complex and diverse features, serving as a crucial basis for arrhythmia diagnosis. The subtle differences in characteristics among various types of arrhythmias, coupled with class imbalance issues in datasets, often hinder existing models from effectively capturing key information within these complex signals, leading to a bias towards normal classes. To address these challenges, this paper proposes a method for arrhythmia classification based on a multi-branch, multi-head attention temporal convolutional network (MB-MHA-TCN).
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