Biological engineers have demonstrated a way to easily retrieve data files stored as DNA. This could be a step toward using DNA archives to store enormous quantities of photos, images, and other digital content.
More researchers and companies are moving into the brain-computer interfaces, yet major challenges remain, from user training to the reality of invasive brain implant procedures.
Machine learning can be used to fill a significant gap in Canadian public health data related to ethnicity and Aboriginal status, according to research by a University of Alberta research epidemiologist.
Scientists have used machin -learning to organize the chemical diversity found in the ever-growing databases for the popular metal-organic framework materials.
In the next-generation operating room interconnected sensors will collect data, analyse it in real-time and make it available to digital assistance functions.
Researchers have shown that federated learning is successful in the context of brain imaging, by being able to analyze MRI scans of brain tumor patients and distinguish healthy brain tissue from cancerous regions.
Newer concepts like edge computing are regularly discussed alongside the cloud within the healthcare sector, often as if they are each exclusive approaches to infrastructure. However, using one does not eradicate the ability to utilise the other.
Using a computer algorithm, scientists at Uppsala University have identified a promising new treatment for neuroblastoma.
An AI platform can analyze genomic data extremely quickly, picking out key patterns to classify different types of colorectal tumors and improve the drug discovery process.
Researchers show that deep learning algorithms perform similar to human experts when classifying blood samples from patients suffering from acute myeloid leukemia.
A video recording of an infant lying in bed can be analyzed with artificial intelligence to extract quantitative information useful for assessing the child’s development as well as the efficacy of ongoing therapy.
A team of experts led by two University of Michigan researchers calls for attention to this shadow record.
Researchers use the analogy of raindrops on the sidewalk to explain their new method to identify genetic variations that cause severe pediatric diseases.
The use of blockchain will change paradigm towards patient-centered healthcare.