(Deep) Learning from Kaggle Competitions. I would like to get more practice with deeplearning. Kaggle is great learning environment, partially because it provides a lot of interesting data.
Technology has touched every one of our lives in very different and impactful ways. Perhaps the biggest impact the advancement of technology has had is in the medical science field. If you are curious about what the future holds for the healthcare technology and some promising trends emerging in
Today, I’d like to share my thoughts on how they apply to people in the medical field and what they want to achieve by acquiring programming skills.
Machine Learning in Medicine: Learning to Trust. In todays technology-based healthcare culture, demand is mounting for medical professionals to place their trust in deep learning.
‘Plug-and-Play’ Control Brain Computer Interfaces Have Arrived. Researchers develop the first self-learning BCI platform that doesn’t require daily recalibration.
In this article, I’m going to explain my experiments with the Kaggle dataset “Chest X-ray Images (Pneumonia)” and how I tackled different problems in this journey which led to getting the perfect accuracy on the validation set and test sets.
Tutorial hell is very real. In this article, we will therefore discuss the most severe one and strategies to avoid it.
We will go through findings that should make you suspicious that there might be something wrong with an article and that you should take an even closer look.
We caught up with Heather Couture, from Pixel Scientia Labs, and she shared insights from her recent research on using deep learning on H&E slides to screen for cancer biomarkers.
AI Ethics: First Do No Harm. AI scientists are mirroring human flaws in the AI universe — after all, robots reflect their creator. We know from research in behavioral economics that humans have innate biases.
The sometimes confusing concepts involved in interpreting coronavirus testing. How do we evaluate how well a machine learning classifier or test model performs? How do we know if a medical test is reliable enough to use in a clinical setting?
Perhaps one of the strangest differences between television in the United States of America, versus other countries, is the abundance of commercials advertising prescription drugs.
Ever since CRISPR was first used to edit human cells in a dish in 2013, scientists have been hopeful about its potential to treat — and hopefully, eliminate — a wide spectrum of genetic diseases.
Millions of people around the world, including around 100,000 in the United States, suffer from sickle cell disease, a brutally painful inherited blood disorder. Most of them are of African descent.
Text mining in the clinical domain has become increasingly important with the number of biomedical documents currently out there with valuable information waiting to be deciphered and optimized by NLP techniques. With the accelerated progress in NLP, pre-trained language models now carry millions (or even billions) of parameters and can leverage massive amounts of textual knowledge
Donated lungs have a short shelf life. After they’re removed from a donor, it’s a race against the clock to get them to a lucky recipient. The delicate, spongy organs are viable for only six to eight hours at most — if they’re suitable for transplant at all.
Urine contains an abundance of dissolved salts and minerals such as calcium and uric acid. These can form crystals, which can grow in size, creating a very painful problem.
Research to possibly speed up the development of vaccines for a virus. In December 2019, the world came to know about a new virus commonly known as coronavirus or scientifically as COVID-19.
‘Our customers want to know who is Apple, and what is it that we stand for,’ Steve Jobs once said. Do we know today? Apple doesn’t typically bungle its marketing.
Find out about what types of software are used in medicine and how it develops the healthcare system