网红黑料

Researchers at 网红黑料 are developing an artificial intelligence algorithm to be used by scientists around the nation who are mapping out the entire human body at the single-cell level.

The project is led by recently hired UF College of Medicine faculty member Pinaki Sarder, Ph.D., an associate professor of quantitative health in the department of medicine and associate director of imaging for UF鈥檚 , or IC3.

Sarder received funding from the National Institutes of 网红黑料 for UF鈥檚 participation in the Human , a network of universities and institutions that submit data to the HuBMAP Data Portal with the goal of creating an open map of the human body at the cellular level. By making these tools and maps widely available, scientists hope to better understand the role of cell and tissue organization and function in human health.

Though scientists are continuously trying to map the human body鈥檚 cell structure, modern advancements allow the researchers using HuBMAP鈥檚 unique collection of data sources to study and learn more about human cells in their different states.

鈥淏y integrating this data, we can better understand the differences between normal and abnormal cell function,鈥� Sarder said. 鈥淒octors should be able to give much more personalized treatment once that is possible.鈥�

UF has secured funding for the next year, during which Sarder鈥檚 team will discern whether an algorithm can be created that could map out the body鈥檚 trillions of cells independently, without the need for a person to input most of the individual data points.

This is a type of machine learning algorithm called a neural network, a complex form of AI that models human brain function by connecting many data points, mimicking the way a brain鈥檚 neurons pass information to various synapses.

鈥淵ou can imagine, with all our organ systems, it isn鈥檛 possible to generate data one by one for each cell without the assistance of this technology,鈥� Sarder said. 鈥淩ight now, we have a big advancement in the possibilities of computing power with the development of these algorithms and neural networks.鈥�

Once Sarder鈥檚 team determines that a machine learning algorithm can be developed to map out cells for a single organ, the NIH will provide funding to expand UF鈥檚 model to different organs and systems using data collected by consortium participants.

鈥淚 feel very privileged to be able to work with some of the top researchers in the U.S. on this,鈥� Sarder said. 鈥淚t is the most challenging and most fascinating work I鈥檝e done yet, and I鈥檓 positive we will make progress on developing this neural network based on the data and information we have available.鈥�