Purpose Artificial intelligence (AI) models are playing an increasing role in biomedical
research and healthcare services. This review focuses on challenges points to be clarified …

One of the key issues facing public healthcare is the global trend of an increasingly ageing
society which continues to present policy makers and caregivers with formidable healthcare …

Big data in health care is a fast-growing field and a new paradigm that is transforming case-
based studies to large-scale, data-driven research. As big data is dependent on the …

Cancer is an aggressive disease with a low median survival rate. Ironically, the treatment
process is long and very costly due to its high recurrence and mortality rates. Accurate early …

Neurological and psychiatric diseases have high degrees of genetic and pathophysiological
heterogeneity, irrespective of clinical manifestations. Traditional medical paradigms have …

A variety of machine learning methods such as naive Bayesian, support vector machines
and more recently deep neural networks are demonstrating their utility for drug discovery …

Since the outbreak of COVID-19, governments have turned their attention to digital contact
tracing. In many countries, public debate has focused on the risks this technology poses to …

Algorithmic biases that favor majority populations pose a key challenge to the application of
machine learning for precision medicine. Here, we assessed such bias in prediction models …

Providing insight into one's health status from a gut microbiome sample is an important
clinical goal in current human microbiome research. Herein, we introduce the Gut …

As bioapplications of 0D and 1D zinc oxide (ZnO) seem a recent development, they have
brought many exciting proposals showing exquisite signs as sensors and assay platforms …