COLLEGE PARK, Md. — The University of Maryland will lead an eight-country research consortium to develop an artificial intelligence-powered early warning system to help communities prepare for and respond to diarrheal disease risks – and potentially other conditions – worsened by extreme weather events.
Biostatistics plays a vital and growing role in the field of public health, providing the analytical foundation for understanding health trends and making evidence-based decisions. As the volume and complexity of health data increases, especially in this new age of artificial intelligence (AI), there is a critical need for biostatistical expertise.
Dr. Huang (Frederick) Lin knows firsthand how artificial intelligence (AI) can support advances in public health: he uses AI daily in his own research analyzing the trillions of microbes living in our guts, looking for those that contribute to major diseases such as inflammatory bowel disease, HIV/AIDS, and various cancers.
Patients with severe mental illnesses (SMI), including schizophrenia spectrum disorder, bipolar disorder, and major depressive disorder, have a greater risk of Alzheimer’s dementia before age 70 due to accelerated brain aging.
In a new study published in Environmental Research Letters, an international team of investigators led by Professor Amir Sapkota offered a way to predict the risk of deadly diarrhea outbreaks using AI modeling, giving public health systems weeks or even months to prepare and to save lives.
Climate change-related extreme weather, such as massive flooding and prolonged drought, often result in dangerous outbreaks of diarrheal diseases particularly in less developed countries, where diarrheal diseases is the third leading cause of death among young children. Now a study out Oct.
