Collaborating Authors

Modelling of Sickle Cell Anemia Patients Response to Hydroxyurea using Artificial Neural Networks Artificial Intelligence

Hydroxyurea (HU) has been shown to be effective in alleviating the symptoms of Sickle Cell Anemia disease. While Hydroxyurea reduces the complications associated with Sickle Cell Anemia in some patients, others do not benefit from this drug and experience deleterious effects since it is also a chemotherapeutic agent. Therefore, to whom, should the administration of HU be considered as a viable option, is the main question asked by the responsible physician. We address this question by developing modeling techniques that can predict a patient's response to HU and therefore spare the non-responsive patients from the unnecessary effects of HU on the values of 22 parameters that can be obtained from blood samples in 122 patients. Using this data, we developed Deep Artificial Neural Network models that can predict with 92.6% accuracy, the final HbF value of a subject after undergoing HU therapy. Our current studies are focussing on forecasting a patient's HbF response, 30 days ahead of time.

We Made Our Own Artificial Intelligence Art, and So Can You


On the 3:13 pm train out of San Jose on a recent Friday, I hunched over a Macbook, brow furrowed. Hundreds of miles north in a Google datacenter in Oregon, a virtual computer sprang to life. I was soon looking at the yawning blackness of a Linux command line--my new AI art studio. Some hours of Googling, mistyped commands, and muttered curses later, I was cranking out eerie portraits. I may reasonably be considered "good" with computers, but I'm no coder; I flunked out of Codecademy's easy-on-beginners online JavaScript course.

New machine learning system can automatically identify shapes of red blood cells


Using a computational approach known as deep learning, scientists have developed a new system to classify the shapes of red blood cells in a patient's blood. The findings, published in PLOS Computational Biology, could potentially help doctors monitor people with sickle cell disease.

AI creates 'sexy' nude portraits and the results are horrifying

Daily Mail - Science & tech

An artificially intelligent (AI) machine that creates surreal nude portraits has been built by a teenager in Virginia. AI whiz Robbie Barrat fed a neural network - an AI that functions like the human brain - thousands of naked portraits and then trained it to create its own racy artworks. In a Twitter post, he said the software often paints people as fleshy blobs spouting random tendrils and limbs, adding: 'I wonder if that's how machines see us'. While most of the women in the images appear lumpy and misshapen, some of the subjects closely resemble slender, standing figures. Mr Barrat, who recently graduated high school in West Virginia, said he is currently doing'deep learning interning' for AI computing giant NVIDIA.

Automated screening of sickle cells using a smartphone-based microscope and deep learning


Sickle cell disease (SCD) is a major public health priority throughout much of the world, affecting millions of people. In many regions, particularly those in resource-limited settings, SCD is not consistently diagnosed. In Africa, where the majority of SCD patients reside, more than 50% of the 0.2–0.3 million children born with SCD each year will die from it; many of these deaths are in fact preventable with correct diagnosis and treatment. Here, we present a deep learning framework which can perform automatic screening of sickle cells in blood smears using a smartphone microscope. This framework uses two distinct, complementary deep neural networks.