… In this study, we hypothesize that the continued integration of pharmacogenomics, clinical
genomics, AI, and healthcare will allow for increased potential in patient diagnosis and …

… Several works have applied artificial intelligence and machine learning methods to predict
future medical outcomes based on the current patient clinical and illness status. In this review, …

… with genomic and pharmacogenomic analyses combined with personal health and … ; to
demonstrate the value of personalized medicine approaches on public health outcomes. …

… Integration of artificial intelligence (AI) approaches such as machine learning, deep learning,
… We believe that AI will remain the main driver to healthcare transformation toward precision …

… many important subfields of artificial intelligence over the last … approaches for knowledge
extraction in pharmacogenomics … pharmacogenomic response, prediction of drug–genome …

… Pharmacogenomics is the aspect of clinical genomics that … of the healthcare team also
cries out for novel approaches—… to apply artificial intelligence and machine learning to create …

… a clinical genomic signature for novel drug discovery and target prediction in health omics. …
prevalent in mendelian disease prediction, pharmacogenomics, and precision oncology. …

… at baseline, 4 and 8 weeks, as well as genomic data. The … and in healthcare more broadly
should be acknowledged … with machine learning and other artificial intelligence approaches to …

… We propose to apply the principles artificial intelligence to develop a medication … the tailoring
of medical treatment to the individual characteristics of each patient. The approach relies on …

… Methods embodying artificial intelligence play a crucial role … the power of clinical and
genome-wide genomic data have … medical centers and health systems that are implementing …