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Rad4XCNN: A new agnostic method for post-hoc global explanation of CNN-derived features by means of Radiomics.
Comput Methods Programs Biomed
January 2025
Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University of Palermo, Palermo, 90127, Italy. Electronic address:
Article Synopsis
- Machine learning-based clinical decision support systems (CDSS) face challenges with transparency and reliability, as explainability often reduces predictive accuracy.
- A novel method called Rad4XCNN enhances the predictive power of CNN features while maintaining interpretability through Radiomics, moving beyond traditional saliency maps.
- In breast cancer classification tasks, Rad4XCNN demonstrates superior accuracy compared to other feature types and allows for global insights, effectively addressing the explainability-accuracy trade-off in AI models.
Demystifying Volume Status: An Ultrasound-Guided Physiologic Framework.
Chest
January 2025
Department of Medicine, University of British Columbia. Electronic address:
Topic Importance: Accurate assessment of a patient's volume status is crucial in many conditions, informing decisions on fluid prescribing, vasoactive agents, and decongestive therapies. Determining a patient's volume status is challenging, due to limitations in examination and investigations and the complexities of fluid homeostasis in disease states. Point-of-care ultrasound (POCUS) is useful in assessing hemodynamic parameters related to volume status, fluid responsiveness, and fluid tolerance.
View Article and Find Full Text PDF2025 Expert Consensus Recommendations for the Diagnostic Requirements in Routine Practices of Transthoracic Echocardiography.
Acta Cardiol Sin
January 2025
Division of Cardiology, Department of Internal Medicine, China Medical University Hospital and College of Medicine, China Medical University, Taichung.
Transthoracic echocardiography plays a crucial role in clinical diagnosis and is increasingly being used around the world. Comprehensive echocardiographic examinations require accurate measurements and the operators to have excellent technical skills. Despite the availability of several published echocardiographic guidelines, the absence of recommended operational manuals in daily practice has resulted in significant variation in the content of echocardiography reports across different medical institutions.
View Article and Find Full Text PDFApplications of Artificial Intelligence in Gastrointestinal Endoscopic Ultrasound: Current Developments, Limitations and Future Directions.
Cancers (Basel)
December 2024
Digestive Diseases and Surgery Institute, Cleveland Clinic, London SW1X 7HY, UK.
Endoscopic ultrasound (EUS) effectively diagnoses malignant and pre-malignant gastrointestinal lesions. In the past few years, artificial intelligence (AI) has shown promising results in enhancing EUS sensitivity and accuracy, particularly for subepithelial lesions (SELs) like gastrointestinal stromal tumors (GISTs). Furthermore, AI models have shown high accuracy in predicting malignancy in gastric GISTs and distinguishing between benign and malignant intraductal papillary mucinous neoplasms (IPMNs).
View Article and Find Full Text PDFImportance of EQA/PT for the detection of genetic variants in comprehensive cancer genome testing.
Sci Rep
January 2025
Genetic Analysis Department, Tsukiji Registered Clinical Laboratory, Riken Genesis Co., Ltd., Tokyo, Japan.
Comprehensive genomic profiling (CGP) is increasingly used as a clinical laboratory test and being applied to cancer treatment; however, standardization and external quality assessments (EQA) have not been fully developed. This study performed cost-effective EQA and proficiency tests (PT) for CGP testing among multiple institutions those belong to the EQA working group of Japan Association for Clinical Laboratory Science (JACLS). This study revealed that preanalytical processes, such as derived nucleic acids (NA) extraction from formalin fixed paraffine embedded (FFPE) samples, are critical.
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