Lifeboat Foundation

Skin wounds that don’t heal properly can lead to dangerous, painful infections. Taking care of injured skin can help prevent problems.

Imagine that a soldier has a tiny computer device injected into their bloodstream that can be guided with a magnet to specific regions of their brain. With training, the soldier could then control weapon systems thousands of miles away using their thoughts alone. Embedding a similar type of computer in a soldier’s brain could suppress their fear and anxiety, allowing them to carry out combat missions more efficiently. Going one step further, a device equipped with an artificial intelligence system could directly control a soldier’s behavior by predicting what options they would choose in their current situation.

While these examples may sound like science fiction, the science to develop neurotechnologies like these is already in development. Brain-computer interfaces, or BCI, are technologies that decode and transmit brain signals to an external device to carry out a desired action. Basically, a user would only need to think about what they want to do, and a computer would do it for them.

BCIs are currently being tested in people with severe neuromuscular disorders to help them recover everyday functions like communication and mobility. For example, patients can turn on a light switch by visualizing the action and having a BCI decode their brain signals and transmit it to the switch. Likewise, patients can focus on specific letters, words or phrases on a computer screen that a BCI can move a cursor to select.

The challenge: There are very few ways to slow down Alzheimer’s disease or treat its symptoms, and there’s no cure — in 2021, nearly 120,000 Americans died from Alzheimer’s complications, making it one of the top 10 leading causes of death.

One genetic variant in particular — called APOE-e4 — is strongly tied to the brain disease. Having one copy makes a person 2–3 times more likely to develop Alzheimer’s, while having two copies (one from each parent) increases the risk by 8–12 times.

Rohit Singla, an MD/PhD student, shares how his training in both medicine and engineering is allowing him to identify complex problems, understand the nuances within them and tackle those complex problems with elegant solutions that are the right fit for patients with kidney disease. Using data from over 10,000 cases, he is creating artificial intelligence tools to automatically detect microscopic changes in the kidney structure and develop new treatments to improve people’s lives.

Produced by UBC faculty of medicine development and alumni engagement.

Continue reading “Aspire #02 — Rohit Singla: Using AI to Develop New Treatments in Kidney Disease” »

For more information on addiction services at #YaleMedicine, visit: https://www.yalemedicine.org/departments/program-in-addiction-medicine.

Written and produced by Yale Neuroscience PhD student Clara Liao.

Continue reading “How an Addicted Brain Works” »

Speech BCIs that use brain implants and algorithms to translate brain signals into text are changing the lives of people with paralysis.

Two-photon polymerization is a potential method for nanofabrication to integrate nanomaterials based on femtosecond laser-based methods. Challenges in the field of 3D nanoprinting include slow layer-by-layer printing and limited material options as a result of laser-matter interactions.

In a new report now on Science Advances, Chenqi Yi and a team of scientists in Technology Sciences, Medicine, and Industrial Engineering at the Wuhan University China and the Purdue University U.S., showed a new 3D nanoprinting approach known as free-space nanoprinting by using an optical force brush.

This concept allowed them to develop precise and spatial writing paths beyond optical limits to form 4D functional structures. The method facilitated the rapid aggregation and solidification of radicals to facilitate polymerization with increased sensitivity to laser energy, to provide high accuracy, free-space painting much like Chinese brush painting on paper.

#medicalAI

Generative AI for medical imaging can create infinite synthetic images of the human anatomy. These large, synthetic datasets are used for training generalizable AI models that can learn from evolving patient data while preserving patient privacy. Learn how MONAI, a framework for building and deploying medical AI, and partners like King’s College London, Mount Sinai, and East River Imaging are using generative AI to study disease and make AI decisions and predictions more accurate, trusted, and safe.

This video is about How ChatGPT/ AI can disrupt healthcare.

ChatGPT is an AI-powered chat platform developed by OpenAI. It allows users to ask questions in a conversational format and build on previous conversations, which allows for improved learning over time. Microsoft has invested billions of dollars in ChatGPT, integrating it into their search engine Bing and web browser Edge. Although the rise of AI has caused concern over job security, ChatGPT currently requires human input to generate questions and diagnose patients, making it a tool to augment human abilities in healthcare. The technology can be used for diagnosis, research, medical education, and radiographs. It can assist healthcare professionals in diagnosing and researching diseases, visualizing anatomy and procedures, and analyzing medical images.

Continue reading “ChatGPT AI in HEALTHCARE? Innovation and disruption” »