Advanced Mathematics to Advance Patient Care

Machine learning techniques have the potential to provide personalized predictions for individual patients based on their unique medical trajectories. These techniques, combined with big data, to which we are fortunate to have access to here in Pittsburgh, along with the collaboration among the University of Pittsburgh, UPMC, and Carnegie Mellon University, can be helpful in areas such as, predicting disease, events like heart failure and epilepsy attacks, and even in situations where patients prepare for end-of-life care. These systems are expected to change medicine, especially in areas of predictive diagnosing.

Low Vision Center for the Advancement of Independence

This center, which will be an integral part of the new Vision Institute, will allow for the assembly of teams of clinicians, researchers, patients, and community partners focused on the following goals:

1. Evaluation of Needs

Identify patients’ needs and barriers to independent living at home, work and community. We will utilize healthcare specialists who are experts in conducting patient interviews and surveys. From this, we can conduct evaluation of function in specific domains and various environments, such the home or the workplace.

2. Evaluate Current Interventions and Assistive Technology

Patients with low vision use a variety of medical therapies and/or visual assistive devices. Another goal of LoV-CAI is to measure the efficacy of these interventions and to develop metrics for evaluating training, new technologies and their impact on a patient’s performance.

3. Develop New and Innovative Solutions

An important part of creating this Center is the platform it allows us to be able to partner with companies to improve, adapt and extend existing interventions based on what we learn from patients and their experiences.

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