Significant health disparities exist in chronic kidney disease (CKD), CKD progression, and end stage renal disease (ESRD) in ethnically diverse populations. African Americans (AAs) have approximately 25% higher prevalence of CKD, and 3x higher rates of ESRD compared to their counterparts. Moreover, a portion of these individuals exhibit rapid decline, progressing much faster than other comparable patients.

The confluence of machine learning (ML) data-driven approaches and increased computational power, alongside access to the wealth of electronic health records (EHRs) and other emergent types of data (e.g., omics, imaging, mHealth), are accelerating the development of biomedical predictive models. Such models range from traditional statistical approaches (e.g., regression) through to more advanced deep learning techniques (e.g., convolutional neural networks, CNNs), and span different tasks (e.g., biomarker/pathway discovery, diagnostic, prognostic, etc.).

While routine screening has been shown to decrease breast cancer mortality in multiple randomized controlled trials, mammography is limited by subjective human interpretation. Recent advances in improved computer processing power, cloud-based data storage capabilities, and availability of large imaging datasets have led to renewed excitement for applying artificial intelligence (AI) to mammography interpretation.

Stroke is a leading cause of mortality and morbidity in the United States, with approximately 795,000 Americans experiencing a new or recurrent stroke each year. Intravenous tissue plasminogen activator (IV tPA) is the dominant and most proven treatment option, but its use is only indicated within 4.5 hours following a stroke. Unfortunately, up to 30% of stroke patients present with an unknown time since stroke (TSS) symptom onset, which makes them ineligible to receive IV tPA.

The rollout of low-dose computed tomography (LDCT) lung screening programs is accelerating in the United States, aiming for earlier detection of lung cancer to improve long-term survival. However, a consequence of such imaging programs is the increased discovery of indeterminate pulmonary nodules (IPNs). Significant questions remain around the effective management of screen- and incidentally-detected IPNs: while many are benign, a fraction will go on to become cancerous.

Prostate cancer is the second leading cause of cancer death in American men, accounting for 26% of new cancer diagnoses and 9% of cancer deaths in men. Active surveillance, radical prostatectomy and radiotherapy are commonly used treatments for clinically localized prostate cancer. However, current risk stratification methods cannot be used effectively to avoid subjecting patients with clinically indolent cancers to unnecessary interventions, causing significant morbidity and cost.

We are implementing a prototype next-generation decision support system called SmartDx, which learns the optimal sequence of diagnostic tests tailored to a patient’s unique characteristics and circumstances. The goal of this project is to optimize clinical pathways based on diagnostic accuracy, timeliness, and cost for individual patients using routine data collected longitudinally in the electronic health record.

The Los Angeles (LA) PRISMS Center aims to be the leader in the development and application of mobile health (mHealth) technologies that deepen our scientific understanding and clinical management of diseases. Bringing together leading experts from UCLA and the University of Southern California (USC) in biomedical informatics, computer science, wireless health, environmental health science, and pediatrics, this Center supports innovative end-to-end software infrastructure for sensor-based health monitoring.

Annually, it is estimated that more than 795,000 Americans experience a stroke. The severity of neurological damage due to an acute stroke is mitigated by the early restoration of blood flow to the affected area; and more people are now surviving strokes through earlier intervention with thrombolytic agents and interventional clot retrieval devices. Unfortunately, the rapid development of new drugs and devices in this area has made it difficult to provide treatment guidance for a given patient, and metrics for comparing outcomes between treatment groups are lacking.

Intracranial aneurysms (ICAs) are an increasingly common finding, both from incidental discovery on imaging studies and on autopsy; it is estimated that anywhere from 1-6% of the American population will develop this problem. Unfortunately, while our ability to detect ICAs has grown, our fundamental understanding of this disease entity remains lacking and significant debate continues in regards to its treatment.