Health
Responding to growing national health challenges
Johns Hopkins APL is transforming health care by bringing significant new data analytics and systems engineering capability to the field of medicine that will enhance the nation’s ability to predict, prevent, and detect illness and injury.
Related Projects
Army Environmental Health Research
APL and the U.S. Army Center for Environmental Health Research are developing capabilities to detect, assess, and prevent effects from exposure to toxic materials—focusing especially on ways to prevent acute and chronic health effects through new biological technologies.
Durable and Portable Therapeutics Production
APL experts have made significant strides in developing methods for portable production of vaccines and other therapeutics, enabling production on demand in remote locations and during emergency outbreaks.
Eliminating Forever Chemicals
Multiple studies have linked PFAS exposure to harmful health effects in humans and animals, and without a natural way to break them down, the chemicals persist in soil and contaminate the environment — including water. APL scientists are developing several technologies to capture and destroy these “forever chemicals.”
Health Surveillance
APL’s leadership in electronic disease surveillance, both at home and abroad, is making a difference on the front lines of protecting the health of a population.
Mapping the Brain for Machine Learning
APL leads several test and evaluation efforts for the Intelligence Advanced Research Projects Activity’s Machine Intelligence from Cortical Networks (MICrONs) project, launched to develop state-of-the-art machine-learning capabilities by modeling how the brain processes information.
Revolutionizing Prosthetics
Revolutionizing Prosthetics is an ambitious multiyear program—funded by the Defense Advanced Research Projects Agency (DARPA)—to create a neurally controlled artificial limb that will restore near-natural motor and sensory capability to upper-extremity amputee patients.
The Systems Approach to Saving Lives
APL’s thought leaders are stirring discussions on the importance of taking a systems approach to health care.
Related News
News
Jan 16, 2025
At-Home ‘Retinal Selfies’ May Provide a Window on Health
Researchers at Johns Hopkins APL and the Johns Hopkins Medicine Wilmer Eye Institute in Baltimore are designing a retinal imaging platform in the form of wearable eyeglasses that has the potential to expand access to retinal imaging and generate enough data to train machine learning models for accelerated research and improved diagnostic capabilities.
News
Jan 6, 2025
Johns Hopkins APL Reaches Highest Mark for Intellectual Property Disclosures
APL staff members filed a record 564 intellectual property disclosures in fiscal year 2024, reinforcing the Laboratory’s strategic value to sponsors and the nation and demonstrating an initial return on the Laboratory’s multimillion-dollar investments in transforming novel ideas into real and impactful solutions.
Press Release
Jan 3, 2025
Johns Hopkins APL Modeling Tool Affirms Critical Role of Testing in Pandemic Response
APL has contributed to a new study in The Lancet Public Health that found that public-private partnerships to develop, produce and distribute COVID-19 diagnostic tests saved approximately 1.4 million lives and prevented an estimated 7 million patient hospitalizations in the U.S. during the pandemic.
News
Dec 4, 2024
From the Battlefield to Breast Cancer Detection, Johns Hopkins APL Technologies Find Dual Impact
APL researchers used artificial intelligence and two APL-patented imaging technologies to improve the accuracy and efficiency of breast cancer screening. The imaging technologies were originally created for satellite and military applications.
Press Release
Nov 14, 2024
A New Path to Noninvasive Brain-Computer Interface
A new high-resolution neural recording method developed by Johns Hopkins APL and the School of Medicine detects neural activity through the skull at unprecedented resolutions, expanding possibilities for nonsurgical brain-computer interface.