Making an Impact

To date, the CMLH has funded 30 early stage research projects through our sponsorship with UPMC Enterprises. Four projects were funded in 2018 with a special Speech and Language focus. In 2019, an additional five projects were funded in partnership with Amazon Web Services (AWS) through a machine learning research sponsorship. These special projects focused on advancing innovation in areas such as cancer diagnostics, precision medicine, voice-enabled technologies and medical imaging. 

Although many CMLH projects involve data analytics and machine learning, our approach is technology agnostic. We welcome proposals that involve human-computer interaction, language technologies, information systems, computer graphics, computer vision, artificial intelligence, robotics, electrical engineering, economics, psychology, sociology, public policy, business administration, law, design, and any other disciplines that apply to healthcare.

An Overview of the CMLH-Funded Projects:

• Minimally Invasive Classification of Central Nervous System Tumors Using Extracellular Vesicle-Based Liquid Biopsy
• Scaling Remote Extracorporeal Membrane Oxygenation (ECMO) Training With Intelligent Agents
• Smart Sensors for Evaluating and Improving Cochlear Implants
• Improving Breast Cancer Diagnosis With Interpretable Machine Learning
• Machine Learning-Based Localization of Focal Epilepsy From Magnetoencephalography
• Evaluating the Predictive Capability of Machine Learning Algorithms
• Machine Learning Algorithms for Advanced Manufacturing of High Fidelity 3D Printed Biomaterials
• Integrating Deep Learning With High Throughput Materials Engineering for Detecting Noroviruses
• Developing a Biomarker for Alzheimer’s Disease Using Machine Learning and Immune Cell Epigenomics
• Ingestible Impedance Sensors to Acquire Large-Scale Data Sets From Patients with Eosinophilic Esophagitis
• Multimodal Behavioral Screening for Depression
• Diagnosis Coding Engine for Electronic Health Records
• Brain Tsunami’s — Cortical Spreading Depolarizations (CSD’s)
• Deep Learning for Placental Pathology
• Non-Invasive Intracranial Pressure Monitoring
• Sepsis Phenotyping From Electronic Health Records
• Real-Time Tool To Predict Clinical Outcomes After Cardiac Arrest
• Programming Framework for Managing Patient Privacy
• My Healthy Pregnancy
• Phylogenetic Models for Predicting Cancer Progression
• Computational Modeling of Behavioral Rhythms To Predict Readmissions
• Healthcare Trails and Care Coordination Using Admissions, Discharges and Transfers Data
• In-Home Movement Therapy Data Collection
• Detecting Intestinal Activity by Analyzing Gut Sounds
• Clinical Genomics Modeling Platform

Contact the CMLH with any questions regarding the projects. Many detailed descriptions of the projects can be found on the Pittsburgh Health Data Alliance website.