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Computed tomographic coronary artery calcium scanning enables cardiovascular risk stratification; however, exposing patients to high radiation levels is an ongoing concern. New-generation computed tomographic systems use lower radiation doses than older systems do. To quantify comparative doses of radiation exposure, we prospectively acquired images from 220 patients with use of a 64-slice GE LightSpeed VCT scanner (control group, n=110) and a 256-slice GE Revolution scanner (study group, n=110). The groups were matched for age, sex, and body mass index; statistical analysis included t tests and linear regression. The mean dose-length product was 21% lower in the study group than in the control group (60.2 ± 27 vs 75.9 ± 22.6 mGy·cm; P

This study explores the integration of concept bottleneck models (CBMs) with knowledge distillation (KD) while preserving the locality characteristics of the CBM. Although KD proves effective in model compression, compressed models often lack interpretability in their decision-making process. We enhance comprehensive explainability by maintaining CBMs' inherent interpretability through our novel approach to knowledge distillation. We introduce visual concept knowledge distillation (VICO-KD), which transfers both explicit and implicit visual concepts from the teacher to the student model while preserving the local interpretability of the CBM, enabling accurate classification and clear visualization of evidence. VICO-KD demonstrates superior performance on benchmark datasets compared to Vanilla-KD, ensuring the student model learns visual concepts while maintaining the local interpretation capabilities of the teacher CBM. Our methodology shows competitive performance against existing concept models, and the student model, trained via VICO-KD, exhibits enhanced performance compared to the teacher during interventions. This study highlights the effectiveness of combining a CBM with KD to improve both interpretability and explainability in compressed models while maintaining locality properties. [ABSTRACT FROM AUTHOR]

Simple Summary: In this study, a cohort of 95 dogs diagnosed with mammary tumors underwent evaluation through multiple surgical techniques, alongside medication and ovariohysterectomy. The assessment included margin completeness to analyze clinical outcomes. Complete excision of the tumors has been shown to enhance survival time, extend disease-free intervals, and improve the overall well-being of the animals across different clinical stages. The findings suggest that complete surgical excision provides benefits, even in cases where lymphatic invasion is present. Radical mastectomy, which may disrupt potential lymphatic routes for tumor invasion and recurrence, demonstrated better clinical outcomes compared to conservative therapy. However, further investigations are necessary to validate these clinical results and address the side effects associated with radical mastectomy. Despite the possibility of postoperative complications, studies continue to advocate for more radical mastectomies due to their favorable risk-benefit ratio. Additionally, advancements in postoperative treatment can now effectively mitigate many of these complications. This study emphasizes the importance of radical mastectomy in treating malignant mammary tumors in dogs, providing insights that could lead to the development of more effective treatment strategies. The incidence of mammary gland tumors in dogs is a significant issue, characterized by notable rates of malignancy, recurrence, and disease burden. However, the lack of comprehensive information and correlated studies has presented challenges in establishing an effective surgical treatment strategy. In this study, a cohort of 95 dogs diagnosed with mammary tumors underwent evaluation using various surgical methods, medications, ovariohysterectomy, and assessments of margin completeness to analyze clinical outcomes. Significant clinical outcomes were observed following radical mastectomy and conservative surgeries, irrespective of TNM stages and histopathological grade of malignancy. Complete excision demonstrated significantly improved survival time and disease-free interval compared to incomplete excision. It is noted that complete surgical excision provides benefits, even in cases where lymphatic invasion is present. However, further investigations are necessary to validate the clinical results and mitigate side effects from radical mastectomy. Despite postoperative complications, several studies continue to advocate for more radical mastectomies due to their favorable risk-benefit ratio. Moreover, advanced inpatient treatments can now effectively manage or mitigate many of these complications. This study emphasizes the critical role of surgical proficiency and postoperative medication in treating malignant mammary tumors in dogs, and it provides insights that may contribute to the development of more effective treatment strategies for this condition. [ABSTRACT FROM AUTHOR]

Multimodal emotion recognition has emerged as a promising approach to capture the complex nature of human emotions by integrating information from various sources such as physiological signals, visual behavioral cues, and audio-visual content. However, current methods often struggle with effectively processing redundant or conflicting information across modalities and may overlook implicit inter-modal correlations. To address these challenges, this paper presents a novel multimodal emotion recognition framework which integrates audio-visual features with viewers' EEG data to enhance emotion classification accuracy. The proposed approach employs modality-specific encoders to extract spatiotemporal features, which are then aligned through contrastive learning to capture inter-modal relationships. Additionally, cross-modal attention mechanisms are incorporated for effective feature fusion across modalities. The framework, comprising pre-training, fine-tuning, and testing phases, is evaluated on multiple datasets of emotional responses. The experimental results demonstrate that the proposed multimodal approach, which combines audio-visual features with EEG data, is highly effective in recognizing emotions, highlighting its potential for advancing emotion recognition systems. [ABSTRACT FROM AUTHOR]