Clinical Trials are the mandatory path for developing and bringing a new drug or vaccine to the market. Unfortunately, according to a study conducted by MIT, 86 percent of the drugs will fail during this process. This very high failure rate not only has consequences on the Pharmaceutical companies' bottom line, but it precludes potentially safe and efficacious drugs from reaching patients that could benefit from them. Recruitment is one of the main bottlenecks, is time-consuming, and very expensive. According to Chunhua Weng from Columbia University (New York), "Recruitment is the number one barrier to clinical research."
Elon Musk might be well positioned in space travel and electric vehicles, but the world's second-richest person is taking a backseat when it comes to a brain-computer interface (BCI). New York-based Synchron announced Wednesday that it has received approval from the Food and Drug Administration to begin clinical trials of its Stentrode motor neuroprosthesis - a brain implant it is hoped could ultimately be used to cure paralysis. The FDA approved Synchron's Investigational Device Exemption (IDE) application, according to a release, paving the way for an early feasibility study of Stentrode to begin later this year at New York's Mount Sinai Hospital. New York-based Synchron announced Wednesday that it has received FDA approval to begin clinical trials of Stentrode, its brain-computer interface, beating Elon Musk's Neuralink to a crucial benchmark. The study will analyze the safety and efficacy of the device, smaller than a matchstick, in six patients with severe paralysis. Meanwhile, Musk has been touting Neuralink, his brain-implant startup, for several years--most recently showing a video of a monkey with the chip playing Pong using only signals from its brain.
The global surgical robotics market is expanding rapidly and may soon be worth $120B. But is the medical training ecosystem ready for the shift to robot-assisted surgeries? As more surgeons use robots in the OR, the approach for training on them and using them needs to be standardized. The truth is that all surgeons aren't approaching this innovative tech the same way. Standardized best practices are what set surgeons and patients up for success, and will help to make robotic surgery safer in the future.
A federal rule that requires health care providers to offer patients free, convenient and secure electronic access to their personal medical records went into effect earlier this year. However, providing patients with access to clinician notes, test results, progress documentation and other records doesn't automatically equip them to understand those records or make appropriate health decisions based on what they read. "Medicalese" can trip up even the most highly educated layperson, and studies have shown that low health literacy is associated with poor health outcomes. University of Notre Dame researcher John Lalor, an assistant professor of information technology, analytics and operations at the Mendoza College of Business, is part of a team working on a web-based natural language processing system that could increase the health literacy of patients who access their records through a patient portal. NoteAid, a project based at the University of Massachusetts Amherst, conveniently translates medical jargon for health care consumers.
Telemedicine and AI-driven symptom checking has enhanced the first-level diagnosis and prioritizing further. Now that people are willing to accept telehealth, it gains the power to transform the patient-doctor relationship into great heights. According to the latest research, the market for telehealth services is expected to grow by 28% by 2026. Since technology has boosted, the insurance firms are recording increased use cases too. As the life expectancy increases around the world by 2050, it is reported that one-quarter of people in Europe and North America will be over the age of 65 by then, and so the demand on healthcare systems becomes out of ordinary.
Several artificial intelligence algorithms developed by Epic Systems, the nation's largest electronic health record vendor, are delivering inaccurate or irrelevant information to hospitals about the care of seriously ill patients, contrasting sharply with the company's published claims, a STAT investigation found. Employees of several major health systems said they were particularly concerned about Epic's algorithm for predicting sepsis, a life-threatening complication of infection. The algorithm, they said, routinely fails to identify the condition in advance, and triggers frequent false alarms. Some hospitals reported a benefit for patients after fine-tuning the model, but that process took at least a year. Unlock this article by subscribing to STAT and enjoy your first 30 days free!
ComArtSci Associate Professor of Communication Jingbo Meng wanted to see just how effective artificial intelligence (AI) chatbots could be in delivering supportive messages. So she set up the research and used a chatbot development platform to test it out. "Chatbots have been widely applied in customer service through text- or voice-based communication," she said. "It's a natural extension to think about how AI chatbots can play a role in providing empathy after listening to someone's stories and concerns." In early 2019, Meng began assessing the effectiveness of empathic chatbots by comparing them with human chat.
A multi-institutional, international team of researchers at the Georgia Institute of Technology combined wireless soft scalp electronics and virtual reality in a BMI system that allows the user to imagine an action and wirelessly control a wheelchair or robotic arm. The major advantage of this system to the user, compared to what currently exists, is that it is soft and comfortable to wear, and doesn't have any wires. BMI systems are a rehabilitation technology that analyzes a person's brain signals and translates that neural activity into commands, turning intentions into actions. The most common non-invasive method for acquiring those signals is ElectroEncephaloGraphy, EEG, which typically requires a cumbersome electrode skull cap and a tangled web of wires. These devices generally rely heavily on gels and pastes to help maintain skin contact, require extensive set-up times, are generally inconvenient and uncomfortable to use.
Summary: Researchers created a new human brain model using machine learning-based optimization of required user profile information. We all like to think that we know ourselves best, but, given that our brain activity is largely governed by our subconscious mind, it is probably our brain that knows us better! While this is only a hypothesis, researchers from Japan have already proposed a content recommendation system that assumes this to be true. Essentially, such a system makes use of its user's brain signals (acquired using, say, an MRI scan) when exposed to particular content and eventually, by exploring various users and contents, builds up a general model of brain activity. "Once we obtain the'ultimate' brain model, we should be able to perfectly estimate the brain activity of a person exposed to a specific content," says Prof. Ryoichi Shinkuma from Shibaura Institute of Technology, Japan, who was a part of the team that came up with the idea.