University of Texas at Dallas researchers have developed biosensor technology that when combined with artificial intelligence (AI) shows promise for detecting lung cancer through breath analysis.

The electrochemical biosensor identifies eight volatile organic compounds (VOCs) that are potential biomarkers for thoracic cancers, which include lung and esophageal cancers.

Despite enormous progress in the past two decades, the intentional control of bionic prostheses remains a challenge and the subject of intensive research. Now, scientists at the Medical University of Vienna and Imperial College London have developed a new method for precisely detecting the nerve signals remaining after an arm amputation and utilising them to control an artificial arm.

New work by a University of Illinois Urbana-Champaign scholar harnesses the power of generative artificial intelligence, using it in tandem with measurement-based care and access-to-care models in a simulated case study, creating a novel framework that promotes personalized mental health treatment, addresses common access barriers and improves outcomes for diverse individuals.

A team from the Department of Electronics, Information and Bioengineering of the Politecnico di Milano, led by dr. Andrea Moglia, has developed the first online application that helps us understand which Artificial Intelligence model is best suited to create 3D images of every individual organ. This makes treatment of the patient more accurate and reliable.

In a new study, University of Arizona researchers created a model for cutaneous squamous cell carcinoma, a type of skin cancer, and identified two mutated tumor proteins, or neoantigens, that contain features of good candidates for a vaccine. At the same time, they used artificial intelligence to create 3D models to help them understand and predict which neoantigens could provoke T cells, a type of white blood cell critical to the immune system, to attack the cancer.

Scientists at ARUP Laboratories have developed an artificial intelligence (AI) tool that detects intestinal parasites in stool samples more quickly and accurately than traditional methods, potentially transforming how labs diagnose parasitic infections around the world.

Identifying parasites under the microscope has long been a painstaking task requiring highly trained experts to manually scour each sample for telltale cysts, eggs or larva.

A study published in the British Journal of Health Psychology reveals the negative behavioral and psychological consequences of commercial fitness apps reported by users on social media. These impacts may undermine the potential of apps to promote health and wellbeing.

When investigators used artificial intelligence (AI) using a method called Machine-Assisted Topic Analysis (MATA), which combines AI-powered topic modelling with human qualitative analysis,