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Systems and methods for efficient prediction and design of neural stimulation
Unmet Need Bioelectronic therapy is the ability to deliver various electrical impulses to patients through implanted medical devices. These devices can treat heart failure, epilepsy, and chronic pain among other ailments. Depending on the disease,…
EEG-based monitoring of brain recovery following stroke
Unmet Need Stroke is the third leading cause of disability in the US, affecting 800,000 annually. Stroke occurs when blood supply to the brain is impeded, leading to brain damage. Currently, recovery from stroke is…
Alzheimer’s Disease Risk Calculator
Unmet Need About 10% of people above the age of 65 have Alzheimer’s disease (AD). AD varies significantly across patients, both in initial presentation and severity, as well as in the rate of disease progression.…
A multi-electrode multiplexed channel brain-computer interface for patient assistive technologies
Unmet Need According to the WHO, in 2019 neurological disorders were recognized as a growing public health challenge resulting in over 500,000 deaths globally. In the US alone, neurological diseases cause an estimated $800 billion-dollar…
Reducing emergency department crowding through machine learning technology
Unmet Need Over the last 40 years, the number of hospitals and hospital beds in the U.S. has declined, while the demand for emergency department services has increased. As a result, emergency department crowding has…
Laser surgery targeting and guidance system
Unmet Need Lasers are frequently used in surgery, particularly in dermatology and oncology, to excise harmful tissue from the body. However, due to the difficulties in guiding laser surgical instruments, these tools may fail to…
An artificial intelligence powered direct prediction model of machine parameters to enhance patient specific pre-treatment during radiation therapy
Unmet Need Intensity modulated radiation therapy (IMRT) and volumetric modulated radiation therapy (VMAT) are commonly used radiation therapy techniques that are characterized by their highly conformal dose distributions and require pre-treatment quality assurance to ensure…
Smart microscope for diagnosing disease
Value Proposition Since its invention, the microscope has been optimized for interpretation by a human observer. Recently, however, deep learning algorithms have been developed for automated image analysis in a variety of important contexts, such…
Leveraging machine learning to predict and prevent poor health outcomes
Value Proposition Problem behaviors are the leading preventable causes of death and disability in the U.S. Cigarette smoking, for instance, is responsible for over 480,000 deaths in the U.S. every year, and obesity is responsible…
Machine learning algorithm to improve performance of hearing aids and cochlear implants in reverberant environments
Unmet Need In the US, nearly 30 million adults require assistive hearing technology such as hearing aids and cochlear implants. Even with assistive devices, hearing impaired individuals have particular trouble with speech recognition in reverberant…
Parametrization of fractal signature data
The risk of knee osteoarthritis progression can be predicted from the subtle characteristics revealed on a knee radiograph of the subchondral bone, i.e. bone that underlies the articular cartilage. This technology is software code to…
Algorithms for analysis of knee radiographs
Value Proposition Knee osteoarthritis accounts affects at least 19% of American adults aged 45 years and older. It is a disabling joint disease with causes that remain poorly understood but are commonly attributed to aging…