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Breast cancer risk prediction technology using genomic classifier
Unmet Need The earliest form of breast cancer, ductal carcinoma in situ (DCIS), is diagnosed in almost 50,000 people in the U.S. each year. DCIS is considered noninvasive, as abnormal cells have not spread out…
Fiber optic probe with integrated photodetector capabilities
Unmet Need Light-based diagnostics is a non-intrusive procedure that can be used to monitor chemotherapy treatment efficacy. Optical imaging additionally has the capacity for roles in diagnosis and surgery guidance. Currently, many devices for optic…
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…
Machine learning algorithm to predict malignancy in thyroid nodules
Value Proposition An estimated 10% of the general population in the United States are expected to develop a thyroid nodule in their lifetime. Although the vast majority of thyroid nodules are noncancerous, a small proportion…
System and method for training radiation treatment planners using knowledge-based models
Unmet Need Cancer is a leading cause of death worldwide, with almost 10 million deaths and over 19 million new cases in 2020. These numbers are expected to grow, with 28 million new cases estimated…
Systems and methods for learning and accumulating optimal strategies for radiation treatment planning
Unmet Need Cancer is a leading cause of death worldwide, with almost 10 million deaths and over 19 million new cases in 2020. These numbers are expected to grow, with 28 million new cases estimated…
Systems and methods for automatic radiation treatment plan generation and evidence-based customization for breast cancer
Unmet Need Breast cancer is now the most commonly diagnosed form of the disease, with 2.3 million new cases in 2020. Some of the most effective therapies for cancer are based around beams of radiation…
System and method for automated fluence map prediction and radiation treatment plan generation
Unmet Need Cancer is a leading cause of death worldwide, with almost 10 million deaths and over 19 million new cases in 2020. These numbers are expected to grow, with 28 million new cases estimated…
Systems and methods for automated radiation treatment planning with decision support
Unmet Need Cancer is a leading cause of death worldwide, with almost 10 million deaths and over 19 million new cases in 2020. These numbers are expected to grow, with 28 million new cases estimated…
A machine learning model to assess colorectal cancer risk using whole blood samples
Unmet Need Colorectal cancer is the third most commonly occurring cancer in men and the second in women. Early detection and treatment have contributed to an overall dropping of the death rate for several decades,…
A system and method for planning radiosurgery treatments that can better target multiple tumors simultaneously
Unmet Need Brain metastases are the most common neurological complication of primary cancer and are estimated to occur in 9-17% of all cancer patients. Radiosurgery has become a standard treatment technique for brain metastases, which…
Performing tissue discrimination for cancer diagnostics using X-ray diffraction imaging
Value Proposition Cancer diagnosis is a multi-step process involving a variety of specialties. Radiologists use macroscopic imaging systems to determine where to look for potential cancer, while pathologists use microscopic imaging to confirm cancer at…