Therapeutic Area

A group of high school students was one of the top teams to emerge from the recent AI Tech Sprint by the Department of Veterans Affairs, delivering a web application that could help match cancer patients to clinical trials. The three students from Northern Virginia entered their work in a competition that included software companies like Oracle Healthcare and MyCancerDB. Digital consulting company Composite App took the $20,000 first place prize for its solution -- a tool for helping patients stay on track with their care plan -- but the clinical trials team got an honorable mention. The tech sprint was organized by the VA's new AI institute, and it focused on partnering with outside organizations and companies interested in applying artificial intelligence tools and techniques to VA data. The high school team's members -- Shreeja Kikkisetti, Ethan Ocasio and Neeyanth Kopparapu -- met as part of the Northern Virginia-based nonprofit Girls Computing League.

As an aspiring data scientist, the best way for you to increase your skill level is by practicing. And what better way is there for practicing your technical skills than making projects. Personal projects are a really important part of your career's growth. They will take you one step closer to your data science dream. Projects will boost your knowledge, skills, and confidence.

A technology company uses artificial intelligence to assist in cancer drug development has launched a study that will collect data on up to 1,000 blood cancer patients over the course of a year. San Francisco-based Notable said Wednesday it had launched the study, titled ANSWer, which will collect de-identified specimens with matched clinical data from participants in U.S. and Canadian clinical networks, at the time of their entry into the study and during subsequent visits. Patients with acute myeloid leukemia, acute lymphoblastic leukemia, chronic myelogenous leukemia, multiple myeloma, lymphomas, myeloproliferative disorders and others will be included. The goal is to establish a tumor registry with annotated clinical outcomes. "The observational clinical trial that we're kicking off will give us the opportunity to test more patients than ever before, allowing us to continue increasing the platform's predictive value," Notable CEO Matt De Silva said in a statement.

On a chilly evening last fall, I stared into nothingness out of the floor-to-ceiling windows in my office on the outskirts of Harvard's campus. As a purplish-red sun set, I sat brooding over my dataset on rat brains. I thought of the cold windowless rooms in downtown Boston, home to Harvard's high-performance computing center, where computer servers were holding on to a precious 48 terabytes of my data. I have recorded the 13 trillion numbers in this dataset as part of my Ph.D. experiments, asking how the visual parts of the rat brain respond to movement. Printed on paper, the dataset would fill 116 billion pages, double-spaced. When I recently finished writing the story of my data, the magnum opus fit on fewer than two dozen printed pages. Performing the experiments turned out to be the easy part. I had spent the last year agonizing over the data, observing and asking questions. The answers left out large chunks that did not pertain to the questions, like a map leaves out irrelevant details of a territory.

We need better ways to help people. What's the medical breakthrough that could save the most lives in the U.S. over the next ten years? In the 2020s, medical research will likely inch forward when it comes to major killers like heart disease and cancer. But the biggest potential to save lives could lie in learning to prevent suicide. The rates of reported suicides have been creeping up over the last two decades.

Diabetes Professional Care Charity of the year, X-PERT Health, has appointed digital healthcare agency, Pulse, to transform their ground-breaking diabetes education programme onto a digital platform. The new platform, which will be accessible via an app or website, will enable X-PERT Health to scale up its current group based programme, allowing hundreds of thousands more patients to develop the knowledge, understanding and confidence to make lifestyle changes to prevent or manage Type 2 diabetes, further strengthening X-PERT Health's'educate not medicate' philosophy. The educational content will be interactive and engaging, including animated videos, games and quizzes to support discovery learning in a fun and easy-to-use way. The digital programme will also include features such as real-time tracking for diet, physical activity, health results, medication requirement and mood and sleep – helping users to manage and improve their lifestyle and health. This information can then be shared with the users' healthcare professional as part of their regular check-up.

Researchers have successfully applied AI in radiology to identify findings either detectable or not by the human eye. Radiology is now moving from a subjective perceptual skill to a more objective science.2,3 In Radiation Oncology, AI has been successfully applied to automatic tumor and organ segmentation,4–6 78 and tumor monitoring during the treatment for adaptive treatment. In 2012, a Dutch researcher, Lambin P, proposed the concept of "Radiomics" for the first time and defined it as follows: the extraction of a large number of image features from radiation images with a high-throughput approach.9 As AI became more popular and also more medical images than ever have been generated, these are good reason for radiomics to evolve rapidly.

You may think that artificial intelligence (AI) will make doctors obsolete soon but that day is still far off. In fact, computers are not that intelligent just yet. Most computer solutions emerging in healthcare rely on algorithms written to analyse data and recommend treatments. They do not rely on computers thinking independently. The computers in question are fed with large amounts of known data and use rules or algorithms set by experts to extract information and apply it to a health issue or problem.

A remarkable combination of artificial intelligence (AI) and biology has produced the world's first "living robots." This week, a research team of roboticists and scientists published their recipe for making a new lifeform called xenobots from stem cells. The term "xeno" comes from the frog cells (Xenopus laevis) used to make them. One of the researchers described the creation as "neither a traditional robot nor a known species of animal," but a "new class of artifact: a living, programmable organism." Xenobots are less than 1 millimeter long and made of 500-1,000 living cells.

PNNL scientists working with Stanford researchers have put forth a new approach to incorporate medical knowledge into AI systems, improving the accuracy of patient diagnosis dramatically. Artificial intelligence will never replace a doctor. However, researchers at the Department of Energy's Pacific Northwest National Laboratory have taken a big step toward the day when AI can help physicians predict medical events. A new approach developed by PNNL scientists improves the accuracy of patient diagnosis up to 20 percent when compared to other embedding approaches. The PNNL approach seeks to capture and recreate the types of connections physicians do naturally when they apply a lifetime of learning and knowledge to the patient standing in front of them in the exam room.