Named entity recognition on bio-medical literature documents using hybrid based approach

Toward an open access genomics database of South Africans: ethical considerations

Genomics research holds the potential to improve healthcare. Yet, a very low percentage of the genomic data used in genomics research internationally relates to persons of African origin. Establishing a large-scale, open access genomics database of South Africans may contribute to solving this problem. However, this raises various ethics concerns, including privacy expectations and informed consent. The concept of open consent offers a potential solution to these concerns by (a) being explicit about the research participant's data being in the public domain and the associated privacy risks, and (b) setting a higher-than-usual benchmark for informed consent by making use of the objective assessment of prospective research participants' understanding. Furthermore, in the South African context-where local culture is infused with Ubuntu and its relational view of personhood-community engagement is vital for establishing and maintaining an open access genomics database of South Africans. The South African National Health Research Ethics Council is called upon to provide guidelines for genomics researchers-based on open consent and community engagement-on how to plan and implement open access genomics projects.

Artificial Intelligence and Cardiovascular Genetics

Polygenic diseases, which are genetic disorders caused by the combined action of multiple genes, pose unique and significant challenges for the diagnosis and management of affected patients. A major goal of cardiovascular medicine has been to understand how genetic variation leads to the clinical heterogeneity seen in polygenic cardiovascular diseases (CVDs). Recent advances and emerging technologies in artificial intelligence (AI), coupled with the ever-increasing availability of next generation sequencing (NGS) technologies, now provide researchers with unprecedented possibilities for dynamic and complex biological genomic analyses. Combining these technologies may lead to a deeper understanding of heterogeneous polygenic CVDs, better prognostic guidance, and, ultimately, greater personalized medicine. Advances will likely be achieved through increasingly frequent and robust genomic characterization of patients, as well the integration of genomic data with other clinical data, such as cardiac imaging, coronary angiography, and clinical biomarkers. This review discusses the current opportunities and limitations of genomics; provides a brief overview of AI; and identifies the current applications, limitations, and future directions of AI in genomics.