CADI conducts research in computing and engineering technologies that improve health care and surgical processes. Our projects cover several areas in computer assisted medical diagnosis and surgical interventions . Please click any of the images below to learn about our research in the respective domain.
Nowadays finance is inundated with a flurry of data that is increasing in complexity as well as in size. For example, the data covering the quotes and transactions from the major US exchanges (TAQ) grows exponentially, now at a rate of hundreds of terabytes per year. Although there are some parallel computing platforms that facilitate simple requests related to TAQ, there is nothing in place currently having the capacity to handle, more complicated things such as mergers between the TAQ and other potentially large databases.
Characterization of pharmacological signal transductions leading to drug-induced expressions of genes and proteins requires the capability to identify interactions between different potential predictor components, e.g. genomic data, clinical data, and environmental data. Our work primarily focuses on the problem of effective characterization and detection of critical gene-gene and gene-environment interactions associated with the outcomes of interest.
The CADI group is working with the Department of Orthopaedics at UB on simulation-based training modalities for orthopaedic surgery. Orthopaedic surgery deals with complex musculoskeletal structures and mechanical instruments. Algorithms and compute platforms that are perfect to simulate minimally invasive procedures do not scale to orthopaedic surgery.
BIG Data Sets are overwhelming the Discovery Process in science, industry and healthcare. Today, most scientific super-computing is done on parallelized server-based machines. The standard practice of deriving information from raw data typically involves deployment of a data warehouse system exclusively for data storage and separate file systems and compute environment for mining and analysis, thus, requiring the data to be moved from a data warehouse to the compute environment for analytics.
CADI has developed an image guided neurosurgery toolkit to produce optimum plans resulting in minimally invasive surgeries. The Computer Assisted Surgery (CAS) engine covers several research and engineering solutions.
The computational requirement of simulation is a combination of the data processed in a model and the time in which processing has to be performed. Brain shift prediction, which involves processing 43,540 elements, takes approximately 20 minutes on a system of six machines.