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.
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.
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.