Many technology companies are working on artificial intelligence systems that can analyze medical data to help diagnose or treat health problems. Such systems raise the question of whether this kind of technology can perform as well as a human doctor. A new study from MIT computer scientists suggests that human doctors provide a dimension that, as yet, artificial intelligence does not. By analyzing doctors’ written notes on intensive-care-unit patients, the researchers found that the doctors’ “gut feelings” about a particular patient’s condition played a significant role in determining how many tests they ordered for the patient. “There’s something about a doctor’s experience, and their years of training and practice, that allows them to know in a more comprehensive sense, beyond just the list of symptoms, whether you’re doing well or you’re not,” says Mohammad Ghassemi, a research affiliate at MIT’s Institute for Medical Engineering and Science (IMES). “They’re tapping into something that the machine may not be seeing.”...

Imaging deep inside biological tissue has long been a significant challenge. That is because light tends to be scattered by complex media such as biological tissue, bouncing around inside until it comes out again at a variety of different angles. This distorts the focus of optical microscopes, reducing both their resolution and imaging depth. Using light of a longer wavelength can help to avoid this scattering, but it also reduces imaging resolution. Now, instead of attempting to avoid scattering, researchers at MIT have developed a technique to use the effect to their advantage. The new technique, which they describe in a paper published in the journal Science, allows them to use light scattering to improve imaging resolution by up to 10 times that of existing systems. Indeed, while conventional microscopes are limited by what is known as the diffraction barrier, which prevents them focusing beyond a given resolution, the new technique allows imaging at “optical super-resolution,” or beyond this diffraction limit....

Muyinatu A. Lediju Bell, a Johns Hopkins engineering professor who designs medical imaging systems that link light, sound, and robotics to produce clearer pictures, was honored today by MIT Technology Review, which placed her on its prestigious 2016 list of 35 Innovators Under 35. The list annually spotlights the nation's most promising young scientists. "Over the years, we've had success in choosing young innovators whose work has been profoundly influential on the direction of human affairs," said Jason Pontin, the magazine's editor in chief and publisher. "Previous winners include Larry Page and Sergey Brin, cofounders of Google; Mark Zuckerberg, cofounder of Facebook; and Jonathan Ive, chief designer of Apple. We're proud of our selections and the variety of achievements they celebrate, and we're proud to add Muyinatu Bell to this prestigious list." Added Bell: "I keep track of people who've been on the list, and I deeply respect their work. It is a great honor to join this amazing group of pioneers and innovators who have changed the world with their technologies."...

Quantum computing and quantum cryptography are expected to give much higher capabilities than their classical counterparts. For example, the computation power in a quantum system may grow at a double exponential rate instead of a classical linear rate due to the different nature of the basic unit, the qubit (quantum bit). Entangled particles enable the unbreakable codes for secure communications. The importance of these technologies motivated the U.S. government to legislate the National Quantum Initiative Act, which authorizes $1.2 billion over the following five years for developing quantum information science. Single photons can be an essential qubit source for these applications. To achieve practical usage, the single photons should be in the telecom wavelengths, which range from 1,260-1,675 nanometers, and the device should be functional at room temperature. To date, only a single fluorescent quantum defect in carbon nanotubes possesses both features simultaneously. However, the precise creation of these single defects has been hampered by preparation methods that require special reactants, are difficult to control, proceed slowly, generate non-emissive defects, or are challenging to scale....