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Overseas Placements

The Oxford Centre for Doctoral Training (CDT) in Healthcare Innovation programme provides an opportunity for up to four third-year CDT students, per cohort, to spend a period of 4-12 weeks at another overseas institution or in a company, where there is a clear case that the placement will directly benefit the doctoral thesis.

A number of students share their experiences below:

 

Ali Maraci, Siemens Corporate Research, Princeton, New Jersey, USA

I spent three months from November 2014 to February 2015 at Siemens Corporate Research in Princeton, New Jersey for a short internship. The focus of the group I joined was on multiple landmark detection and alignment on various imaging modalities. During this time I was supervised by Dr David Liu and worked on 2D and 3D landmark alignment. The focus of my research was development and testing of novel regression techniques for refining multiple landmarks on CT images. The placement allowed me to further develop my programming and problem solving skills in developing solutions for 3D CT images. This experience provided me with invaluable skills and knowledge which will assist me in my DPhil.

Tingting Zhu, the Center for Research on Computation and Society at School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA

From June to August, I participated in my overseas placement at the Center for Research on Computation and Society (CRCS) at School of Engineering and Applied Science in Harvard University. I was supervised by Dr. Edith Law and contributed to the project entitled "Crowdsourcing Time Series Annotations with Expert Communities and Nonexpert Crowds". My work included: 1) testing the different design of deliberation interfaces and develop an optimal solution that enable experts to monitor, debug and improve crowdsourcing processes; by designing a webbased online annotation system to facilitate dynamic serverclient interactions with realtime information retrieval and modifications, and mouse movement tracking functionality. 2) breaking down the complex medical information tasks (such as identifying Intensive Care Unit arrhythmia alarms in electrocardiogram and classifying Electroencephalography sleep staging) into optimal (‘bitesized’) subtasks, crowdsource them
from Amazon Mechanical Turkers, and extract/fuse useful information to maximise the accuracy of downstream classifiers or aggregation tasks. A doctoral consortium paper was submitted to an international conference. A journal article is being prepared as a result of the visit.

Elnaz Gederi, Harvard University and Brigham and Women’s Hospital

During my overseas placement at Harvard University and Brigham and Women’s Hospital (May to July 2013) I worked on two projects under the guidance of professors Adams, Malhotra, Wellman, and Dr. Nemati. The first project was on understanding the underlying physiology of obstructive sleep apnoea by proposing a method for the real-time measurement of the loop gain of the ventilation control feedback loop. The second project was on detecting episodes of microarousals during sleep. These projects were in line with the clinical need of the sleep specialists at the Brigham and Women’s Hospital and they involved using new signal processing, control systems, and machine learning techniques that I will continue to use in my research. This visit initiated collaboration with Harvard Intelligent Probabilistic Systems (HIPS) and Brigham and Women’s Hospital Sleep Medicine groups. It also allowed me to have access to data from research sleep studies. Two papers are being prepared as a result of the visit.

Tom Peach, Minimally Invasive New Technologies (MINT) research group in New York City

During March and April I visited the Minimally Invasive New Technologies (MINT) research group in New York City. The group is affiliated and works very closely with the Cornell University research division of New York Presbyterian Hospital in New York City. The focus of my visit was the continued testing, development and modelling of a novel flow-­diverting device intended for the treatment of brain aneurysms. The placement allowed me to use my well-­‐developed skills in CFD modelling in a new environment with the challenge of using a novel device concept with behaviour that is radically different to devices currently available. I also learnt a number of in-­vitro techniques including phantom manufacture and deployment rehearsal. As a result of the project work, I completed considerable gains in prototype device design and optimisation, and I am preparing a paper detailing the substantial computations performed.

Marco Pimentel, Laboratory for Computational Physiology, Massachusetts Institute of Technology (MIT), Cambridge, MA, US

Over the period of June to August, three projects were undertaken during my overseas placement at the Massachusetts Institute of Technology (MIT), in Professor Roger Mark’s Laboratory for Computational Physiology. I worked under the guidance of Dr. Leo Celi. The main focus areas of these projects were: 1) outcome prediction of traumatic brain injured patients; 2) study the effect of the change in serum chloride during the first 24 hours on Intensive Care Unit (ICU) outcomes; and 3) study the effect of hyperdynamic left ventricular function on ICU outcomes. These were three mutually beneficial projects as they were in line with the clinical and research interests of Boston’s intensivists and MIT researchers, whereas simultaneously allowed me to gain new programming skills and examine different methodologies and data mining approaches that will be useful for the final year of my DPhil. Two of these projects benefited from the use of a large database of detailed clinical data from over 30,000 ICU patients (the MIMIC-II clinical database from the Beth Israel Deaconness Medical Center in Boston, MA), which I will continue to use over the next year. Furthermore, regular visits to local hospitals in Boston provided me with a better understanding on how data are collected from ICU patients, the issues involved in the data collection process, and how this large database is assembled. A joint abstract had been submitted for an International Conference, and two papers are being prepared as a result of the visit.

Sunali Bhatnagar, University of California, Santa Barbara

Over 8 weeks at the University of California, Santa Barbara, and under the supervision of Professor Samir Mitragotri, I was able to fulfil two aims directly relating to my project; (i) Learn and utilise methods used to correlate skin permeability and resistivity developed in the Mitragotri laboratory, and (ii) initiate development of the formulation and assembly of the vaccine laden gel to a commercially viable patch. As well as these project specific aims, I was able to visit the Centre for Bioengineering, and increase my research awareness in the broader field of drug delivery. The outputs of this placement include significant portions of my own doctoral thesis, potential future collaboration with the Mitragotri group, and a joint publication which is currently being prepared.

Alistair Johnson, Center for Comprehensive Informatics (CCI), Emory University, Atlanta, USA

Over the period of July to September three projects were undertaken during my overseas placement at Emory University under the guidance of Professors Saltz and Buchman. The main focus areas of these projects were: 1) determining if patients in the intensive care unit (ICU) were lacking sufficient attention, 2) robustly detecting the onset of a sustained breathing trial and matching respiration estimates to the measured “gold” standard, and 3) prediction of atrial fibrillation. These three projects were mutually beneficial as they were in line with the clinical desires of Emory’s intensivists, while simultaneously requiring the use of time-series analysis techniques which I will rely heavily on for the final year of my DPhil. The placement allowed me to gain access to a considerable body of ICU data which I will continue to analyse over the next year. Moreover, it initiated a collaboration which will lead to us being able to trial predictive alerting systems in a real ICU which uses the same clinical data system as our industrial collaborators (Cerner Corporation). Three papers are being prepared as a result of the visit.

Berkan Sesen, Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, USA

During my placement at the Stanford Biomedical Informatics Research (BMIR) Center, I had the opportunity to work closely with distinguished academics in the fields of Web Ontology Language (OWL), clinical decision support and probabilistic inference. My interactions with these experts resulted in some significant improvements in my clinical decision support platform and motivated a publication in surgical risk assessment. Working closely with Dr Samson Tu, I carried out a comprehensive literature review on how deterministic ontological languages can be extended to support probabilistic inference and consequently led a group discussion on the topic in one of the BMIR research meetings. Following up on the suggestions from Dr Matthew Horridge, I refined my guideline-rule-based inference framework to perform significantly faster. Also, valuable feedback from the departmental members at the end of my research colloquium helped me improve some of the probabilistic techniques that I utilise in my research. Overall, I am very grateful for the financial support of the CDT in realising this visit and I would strongly encourage all CDT students to consider applying to partake in a similar placement opportunity in their chosen institute.

Yee Kai Tee, F.M. Kirby Research Centre at Kennedy Krieger Institute, John Hopkins University, Baltimore, USA

Over the 10-week placement from 24 September to 30 November 2012 at Johns Hopkins University (JHU), two short projects were undertaken under the guidance of Professor Peter van Zijl and Dr Craig Jones. The first project was a pilot study to optimize a chemical exchange saturation transfer (CEST) MRI sequence and develop an analysis tool to study the change of metabolites in calf muscle after tip-toe exercise. The second project was to improve the CEST acquisition method by optimally using the delay in between RF irradiation pulses to collect higher signal-to-noise data for acute stroke study at John Radcliffe Hospital.

These are two mutually beneficial projects because JHU expertise is in MRI sequence development whereas my strengths are data processing and analysis. The placement was a very fruitful visit because it initiated collaboration with JHU in various MRI research areas and enabled me to acquire some useful CEST data for my DPhil and acute stroke studies. Furthermore, it allowed me to gain access to a considerable amount of CEST data JHU collected for other clinical applications. A joint abstract had been submitted for an MRI conference.