Machine learning in cardiology
My PhD focuses on using (convolutional) neural networks in cardiac imaging. My interests mainly include plain X-ray and echocardiography.
Papers
- Pacemaker identification with neural networks - Under peer review
Other links to my work
Renal denervation
I've written a few meta-analyses on renal denervation over the years which have been covered by Forbes Magazine, Motley Fool et cetera.
In summary, don't bother using office blood pressure if you're unblinded, even if you have a control group
Papers
- Quantifying the 3 biases that plague denervation trials - Circ outcomes
- Putting the hype in hypertension - BMJ
- The CONVERGE analysis - predicted the effect size of Symplicity 3 - Heart
Coronary physiology analysis
A recent publication by our group required complex coronary waveform analysis. I created an open source python program for this
Papers
- Impact of PCI on exercise - JACC
Other links to my work
- Physiology analysis software source code - GitHub
Stem cells
Our meta-analysis showing the benefit from cardiac stems cells is alarmingly well correlated to trial quality. Winner of UK Research Paper of the Year
Papers
- DAMASCENE - BMJ
Other meta-analyses
I'm frequently a co-author on studies where due to my familiarity with meta-analysis
Papers
- PFO closure - European Heart Journal
- DAPT in TAVI - Open Heart
- Effect of study design in AF trials - Journal of cardiovascular electrophysiology
CardiologyTrials.org
My website covering the most important trials in cardiovascular medicine. Depressingly out of date.
Imperial eJournals for Chrome
Adds a button to the address bar in Chrome to allow quick access to journals via the College Library's eJournal system
