Find out about the latest happenings at CHOT!
Penn State National Science Foundation Center for Health Organization Transformation
(Penn State CHOT) - An Industry-University Cooperative Research Center
CHOT students participate in both THON and research to support Four Diamond Families
February 2018
THON and Four Diamonds, Conquering
Childhood Cancer

CHOT Students and THON

THON is a student-run philanthropy committed to enhancing the lives of children and families impacted by childhood cancer. The sole beneficiary of the massive THON fundraiser is Four Diamonds, whose mission is conquering childhood cancer by assisting children and their families through superior care, comprehensive support, and innovative research. 

In 2018, THON raised more than $10.1 million to help children and families treated for cancer at Penn State Children's Hospital. Since 1977, THON has raised $156 million to benefit Four Diamonds. CHOT undergrad Lindsay Mitchell (pictured, on left) participated in THON for for 32 hours this year.
CHOT Scholar and Four Diamonds Sponsored Research

Pediatric Bone Tumor Treatment

Scott Tucker, a CHOT Ph.D. Scholar and fifth-year M.D./Ph.D. student at Penn State Hershey, is working as part of a design team toward improving pediatric bone tumor treatment. 
The team's Four Diamonds funded project focuses on using metallic 3D printing to fill bone gaps resulting from bone tumor resection.

Current techniques are limited to pre-designed off-the-shelf implants that often require removal of healthy native tissue to accommodate the implant. Additive manufacturing enables cost efficient, case specific implant design and manufacture with enhanced capabilities to stimulate bone growth. 
For example, the lattice structure featured in a proximal tibial implant design (pictured above on right) is unrealistic to manufacture by traditional means but is well suited for 3D printing using titanium alloy. The design team has focused on implants for three retrospective clinical cases involving the proximal humerus, distal femur, and proximal tibia. The implant designs are slated to be manufactured this spring for mechanical testing to assess if their actual strength matches their theoretical strength. Future extension of this research could lead to cheaper, case-specific implant solutions that spare healthy tissues in pediatric bone tumor cases for better outcomes. 
 Electronic Medical Records and Data Mining
Student Profiles 
Thanh Le: Improving Employee and Patient Health through Population Data Mining

Thanh Le started as a Ph.D. candidate in the College of Information Science and Technology in 2016 and became a CHOT Scholar in 2017. Thanh's research interests involve innovating machine learning methods to integrate electronic health record data with environmental, behavioral, and contextual factor data, among others, for predictive and causal modeling of health risks/outcomes.
Thanh was also a 2017 trainee in the National Institutes of Health's Biomedical Big Data To Knowledge (BD2K) predoctoral training grant. Before coming to Penn State, Thanh received his bachelor of science in computer science and genetics/cell biology at the University of Minnesota, Twin Cities.

Thanh Le's Research. Data mining and machine learning can improve health care quality by supplying clinicians with critical information and predictions. Electronic Medical Records (EMR) - living records of patient health - present unique opportunities and challenges for current machine learning techniques because this data is very rich, yet massive, high-dimensional, and longitudinal. Because of EMR's size and dimensions, popular approaches for learning in EMR requires aggregating data to reduce the size or applying dimensionality reduction techniques. Such methods produce a much more manageable data size suitable for modeling; however, they take away valuable information encoded in the EMR and frequently produce results which do not give care providers more clinical insights.  
Thanh's research focuses on developing latent variable algorithms which can take full advantage of the longitudinal and high-dimensionality characteristics in EMR data to perform data dimensionality reduction while simultaneously producing interpretable results. The general goal of this project is to create a more transparent and efficient machine learning model for use in the medical setting.
Sam Lapp - Master's Student

Outside of engineering, Sam is a musician, runner, and community organizer.
Sam is a first-year master's 
student in the engineering design program. He is interested in design thinking and using design skills to address problems in the developing world. Currently, in addition to working at CHOT, Sam is involved in several engineering projects in the Humanitarian Engineering and Social Entrepreneurship (HESE) and Global Engineering Teams (GET) programs.

For HESE, he is involved in a project aimed at reducing post-harvest losses for rural farmers in Kenya. In the GET program, he is working with students in South Africa and a sponsor in Germany to develop an alignment device to quantify and simplify the dynamic alignment process for lower-limb prosthetics.

For CHOT, Sam is working with IST Ph.D. student Thanh Le to tackle the challenge of exploring different ways of representing longitudinal data. Some methods, such as the Hidden Markov Model, discard the amount of time between events. However, it may be necessary to consider not just the order of events, but their distance in time. Currently, Sam is measuring the ability of state-of-the-art methods to perform useful classifications on the data. This will allow the team to compare new methods developed to the current best available alternatives.
Undergraduate Student Research
Chonghan Lee

Chonghan is an undergraduate student in computer science who is in his second year with CHOT. He is interested in machine learning and social network data. His real-time social network map service implementation is featured on the home page of Penn State CHOT's website. He is also working on the Screenomics project with Dr. Nilam Ram and Ph.D. candidates Agnese Chiatti and Xiao Yang (featured last month). Chonghan is also an undergraduate researcher in the D.A.T.A. Lab working under Dr. Conrad Tucker. 
Rohan Patel

Rohan is a junior at Penn State, double majoring in computer science and mathematics and calls Ahmedabad, India home. He joined Dr. Tucker's D.A.T.A. Lab in the fall of 2017 and was invited to join CHOT in January of this year. Rohan is tasked with implementing practical applications of Ph.D. research with his coding expertise. CHOT is looking forward to the results of his work in the coming semester and beyond.