Graphs and other structured data have come to the forefront in machine learning over the past few years due to the efficacy of novel representation learning methods boosting the prediction performance in various tasks. Representation learning methods...
We report a new learning approach in science and technology through the Qui-Bot HO project: a multidisciplinary and interdisciplinary project developed with the main objective of inclusively increasing interest in computer science engineering among c...
Diabetes is a long-lasting disease triggered by expanded sugar levels in human blood and can affect various organs if left untreated. It contributes to heart disease, kidney issues, damaged nerves, damaged blood vessels, and blindness. Timely disease...
The author presents his view of the start of clinical medical ethics and ideas on where the broader field of bioethics is heading. In addition to clinical medical ethics, people with training in clinical ethics can enlarge the scope of their work in ...
The need to overcome the challenges of visual inspections conducted by domain experts drives the recent surge in visual inspection research. Typical manual industrial data analysis and inspection for defects conducted by trained personnel are expensi...
BACKGROUND AND OBJECTIVES: Artificial intelligence (AI) is widely positioned to become a key element of intelligent technologies used in the long-term care (LTC) for older adults. The increasing relevance and adoption of AI has encouraged debate over...
Neural networks : the official journal of the International Neural Network Society
37149917
Lifelong graph learning deals with the problem of continually adapting graph neural network (GNN) models to changes in evolving graphs. We address two critical challenges of lifelong graph learning in this work: dealing with new classes and tackling ...
Journal of the American Medical Informatics Association : JAMIA
37172264
OBJECTIVE: To retrieve and appraise studies of deployed artificial intelligence (AI)-based sepsis prediction algorithms using systematic methods, identify implementation barriers, enablers, and key decisions and then map these to a novel end-to-end c...
Over the past 20 years, neuroscience has been propelled forward by theory-driven experimentation. We consider the future outlook for the field in the age of big neural data and powerful artificial intelligence models.
Artificial intelligence (AI) could revolutionise health care, potentially improving clinician decision making and patient safety, and reducing the impact of workforce shortages. However, policymakers and regulators have concerns over whether AI and c...