A freely available computer program that takes into account specific local conditions enables users to predict the impact of adopting different diagnostic strategies on the spread of tuberculosis in their region.
PCR testing for SARS-CoV-2 from samples taken from smartphone screens, Phone Screen Testing, provides a sensitive, cost-effective, simple, and non-invasive new method that could boost COVID-19 mass test screening.
Pathogen natural history, epidemiological knowledge, human behavior and epidemic progression determine whether symptom screening and questionnaires are effective barriers to geographic spread of infection by travelers.
A model based on empirical parameter estimates predicts that arresting cancer cell growth by less than 1% per day will produce optimal outcomes in preventing life-threatening cancers, and that such preventive measures are generally more successful than post-diagnostic interventions.
The relationship between blood groups and disease is detangled, without preconceived ideas, using population-wide data, with millions of participants and lifetime follow-up, identifying not only previously known relationships but also new insights.
Application of machine learning to serum miRNA profiles generated through next generation sequencing identifies a biologically relevant miRNA signature which can be deployed as a qPCR test to assist the diagnosis of epithelial ovarian cancer.