Studies in health technology and informatics
Sep 2, 2022
The development of the cognitive framework regarding the current performances of the historic built environment in physical accessibility plays a key role in the definition of inclusive design strategies. To this end, this paper presents the comparis...
Database : the journal of biological databases and curation
Sep 2, 2022
Monitoring drug safety is a central concern throughout the drug life cycle. Information about toxicity and adverse events is generated at every stage of this life cycle, and stakeholders have a strong interest in applying text mining and artificial i...
We present a benchmark study of autonomous, chemical agents exhibiting associative learning of an environmental feature. Associative learning systems have been widely studied in cognitive science and artificial intelligence but are most commonly impl...
Machine learning is the field of artificial intelligence in which computers are trained to make predictions or to identify patterns in data through complex mathematical algorithms. It has great potential in critical care to predict outcomes, such as ...
Detecting protected health information in electronic health record systems is often an early step in health care analytics, and it is a nontrivial problem. Specific challenges include finding clinician names and diseases, which lack a fixed format an...
Diagnostic and interventional radiology (Ankara, Turkey)
Sep 1, 2022
Artificial intelligence (AI) and machine learning (ML) are increasingly used in radiology research to deal with large and complex imaging data sets. Nowadays, ML tools have become easily accessible to anyone. Such a low threshold to accessibility mig...
Immunotherapy offers the potential for durable clinical benefit but calls into question the association between tumor size and outcome that currently forms the basis for imaging-guided treatment. Artificial intelligence (AI) and radiomics allow for d...
In this study, I introduce the use of Bayesian Artificial Intelligence, namely through the probabilistic and structure learning of Bayesian Network models, for hypothesis generation in psychiatry. Bayesian Networks are directed acyclic graphical mode...
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