INTRODUCTION: Dysmorphism is an important characteristic, but its evaluation is largely subjective. A good clinical assessment (dysmorphism) can facilitate a more accurate and efficient diagnosis. We therefore evaluated an automated artificial intell...
International journal of pediatric otorhinolaryngology
Jul 1, 2025
BACKGROUND: Artificial Intelligence (AI) and machine learning (ML) have transformative potential in enhancing diagnostics, treatment planning, and patient management. However, their application in pediatric otolaryngology remains limited as the uniqu...
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jul 1, 2025
PURPOSES: This study aimed to develop a computed tomography (CT)-based multi-organ segmentation model for delineating organs-at-risk (OARs) in pediatric upper abdominal tumors and evaluate its robustness across multiple datasets.
Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
Jul 1, 2025
OBJECTIVE: Pediatric otorhinolaryngology (ORL) addresses complex conditions in children, requiring a tailored approach for patients and families. With artificial intelligence (AI) gaining traction in medical applications, this study evaluates the qua...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Deep learning for Electroencephalography (EEG) has become dominant in the tasks of discrimination and evaluation of brain disorders. However, despite its significant successes, this approach has long been facing challenges due to the limited availabi...
Cardiovascular disease (CVD) is a primary cause of death in India, accounting for a significant portion of the global CVD burden. This study looks at statistics on heart disease mortality from the Institute for Health Metrics and Evaluation (IHME) fr...
Proceedings of the National Academy of Sciences of the United States of America
Jun 10, 2025
The number of acutely food insecure people worldwide has doubled since 2017, increasing demand for early warning systems (EWS) that can predict food emergencies. Advances in computational methods, and the growing availability of near-real time remote...
Deep learning frameworks utilizing convolutional neural networks (CNNs) have frequently been used for brain age prediction and have achieved outstanding performance. Nevertheless, deep learning remains a black box as it is hard to interpret which bra...
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