Knowing who may progress along the disease pathway is critical for early diagnosis and intervention, improved treatment and better disease management, according to a team that has developed a new method to predict the progression of autoimmune disease among those with preclinical symptoms. The team used artificial intelligence (AI) to analyze data from electronic health records and large genetic studies of people with autoimmune disease to come up with a risk prediction score. When compared to existing models, this methodology was between 25% and 1,000% more accurate in determining whose symptoms would move to advanced disease.
Read more …Predicting the progression of autoimmune disease with AI
Neural implants contain integrated circuits (ICs) -- commonly called chips -- built on silicon. These implants need to be small and flexible to mimic circumstances inside the human body. However, the environment within the body is corrosive, which raises concerns about the durability of implantable silicon ICs. A team of researchers address this challenge by studying the degradation mechanisms of silicon ICs in the body and by coating them with soft PDMS elastomers to form body-fluid barriers that offer long-term protection to implantable chips. These findings not only enhance the longevity of implantable ICs but also significantly broaden their applications in the biomedical field.
Read more …Advancements in neural implant research enhance durability