Wiener medizinische Wochenschrift (1946)
Feb 24, 2025
Given how the diagnosis and management of many ocular and, most specifically, retinal diseases heavily rely on various imaging modalities, the introduction of artificial intelligence (AI) into this field has been a logical, inevitable, and successful...
Drawings serve as a profound medium of expression for both humans and apes, offering unique insights into the cognitive and emotional landscapes of the artists, regardless of their species. This study employs artificial intelligence (AI), specificall...
The advances in artificial intelligence (AI) technology in recent years have been remarkable, and the field of radiology is at the forefront of applying and implementing these technologies in daily clinical practice. Radiologists must keep up with th...
International journal of neural systems
Feb 24, 2025
Applications of Artificial Intelligence (AI) are revolutionizing biomedical research and healthcare by offering data-driven predictions that assist in diagnoses. Supervised learning systems are trained on large datasets to predict outcomes for new te...
Entity and relation extraction from Chinese electronic medical records (EMRs) is a crucial foundation for constructing medical knowledge graphs and supporting downstream tasks. Chinese EMRs face challenges in accurately extracting medical entity rela...
Predicting indoor air pollutants concentrations in schools is essential for ensuring a healthy learning environment. Traditional measurements methods pose challenges in cost, maintenance, and time. This study proposes a new approach using a deep lear...
The increasing complexity and interconnectedness of healthcare data present numerous opportunities to improve prediction, diagnosis, and treatment. Graph-structured data, which represents entities and their relationships, is well-suited for modeling ...
Explainability in Medical Computer Vision is one of the most sensible implementations of Artificial Intelligence nowadays in healthcare. In this work, we propose a novel Deep Learning architecture for eXplainable Artificial Intelligence, specially de...
The emergence of single-cell technologies, including flow and mass cytometry, as well as single-cell RNA sequencing, has revolutionized the study of cellular heterogeneity, generating vast datasets rich in biological insights. Despite the effectivene...
The integration of Artificial Intelligence (AI) with the Internet of Medical Things (IoMT) has revolutionized disease prediction and detection, but challenges such as data heterogeneity, privacy concerns, and model generalizability hinder its full po...
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