Nurses typically spend 18 to 40 percent of their time performing direct patient care tasks, oftentimes for many patients and with little time to spare. Personal care robots that brush your hair could provide substantial help and relief.
Search for: Massachusetts Institute of Technology
BrainGate researchers demonstrated the first human use of a wireless transmitter capable of delivering high-bandwidth neural signals.
Researchers have created polymers that replicate the structure of mucins, the molecules that give mucus its unique antimicrobial properties.
Many patients use their inhalers and insulin pens wrong. Researchers have developed a system to reduce those numbers for some types of medications.
Deep learning-based system enables dermatologist-level identification of suspicious skin lesions from smartphone photos, allowing better screening.
The patch, which can be folded around surgical tools, may someday be used in robotic surgery to repair tissues and organs.
Researchers have developed an “organs-on-a-chip” system that replicates interactions between the brain, liver, and colon.
A machine learning system learns on the job. By continuously adapting to new data inputs, this “liquid network” could aid decision-making in medical diagnosis.
Scientists have proposed a new principle by which active matter systems can spontaneously order, without need for higher level instructions or even programmed interaction among the agents.
Researchers have examined how mobile technologies have been used in monitoring and mitigating the effects of the Covid-19 pandemic.
Researchers have developed a way for deep learning neural networks to rapidly estimate confidence levels in their output.
Researchers have shown that they can measure those effects of the Corona pandemic on mental health by analyzing the language that people use to express their anxiety online.
Researchers have found that people who are asymptomatic for Covid-19 may differ from healthy individuals in the way that they cough.
Artificial intelligence is developing at an enormous speed and intelligent instruments will profoundly change surgery and medical interventions.
Scientists have used machin -learning to organize the chemical diversity found in the ever-growing databases for the popular metal-organic framework materials.
Pathologists who examined the computationally stained images could not tell them apart from traditionally stained slides.
A way to incorporate electronic sensors into stretchy fabrics allows scientists to create shirts or other garments that could be used to monitor vital signs such as temperature, respiration, and heart rate.
Researchers have developed a new approach to early diagnosis of lung cancer: a urine test that can detect the presence of proteins linked to the disease.
Interacting with a robotic teddy bear invented at MIT boosted young patients’ positive emotions, engagement, and activity level.
Engineers have designed pliable, 3D printed mesh materials whose flexibility and toughness they can tune to emulate and support softer tissues such as muscles and tendons.
Wearing a sensor-packed glove while handling a variety of objects, researchers have compiled a massive dataset that enables an AI system to recognize objects through touch alone.
Engineers have designed an ingestible pill that quickly swells to the size of a soft, squishy ping-pong ball big enough to stay in the stomach for an extended period of time.
Research from the BrainGate consortium shows that a brain-computer interface (BCI) can enable people with paralysis to directly operate an off-the-shelf tablet device just by thinking about making cursor movements and clicks.
Research project is aimed at improving therapeutic options for both rare and common diseases, including supporting methods to improve editing the human genome.
Researchers employ novel machine learning techniques that determines the fewest, smallest doses of toxic chemotherapy and radiotherapy that could still shrink glioblastomas.
Made of electronic circuits coupled to minute particles, cell-sized robots could flow through intestines or pipelines to detect problems.
Machine learning network offers personalized estimates of children’s behavior.
MIT researchers have built an ingestible sensor equipped with genetically engineered bacteria that can diagnose bleeding in the stomach or other gastrointestinal problems.