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Updates every hour. Last Updated: 20-Jun-2025 17:10 ET (20-Jun-2025 21:10 GMT/UTC)
Artificial intelligence has the potential to improve the analysis of medical image data. For example, algorithms based on deep learning can determine the location and size of tumors. This is the result of AutoPET, an international competition in medical image analysis, where researchers of Karlsruhe Institute of Technology (KIT) were ranked fifth. The seven best autoPET teams report in the journal Nature Machine Intelligence on how algorithms can detect tumor lesions in positron emission tomography (PET) and computed tomography (CT). (DOI: 10.1038/s42256-024-00912-9)
Piezoelectric and triboelectric tactile sensors, crucial for applications in robotics and wearable devices, face challenges in flexibility and environmental resilience. In a new study, researchers have developed innovative manufacturing strategies to enhance sensor performance by optimizing material properties and fabrication techniques. These advancements are set to drive the creation of highly sensitive, self-powered sensors for next-generation technologies, enabling breakthroughs in healthcare, robotics, and human-machine interfaces.
Steroid hormones are among the most widespread aquatic micropollutants. They are harmful to human health, and they cause ecological imbalances in aquatic environments. At the Karlsruhe Institute of Technology (KIT), researchers have investigated how steroid hormones are degraded in an electrochemical membrane reactor with carbon nanotube membranes. They found that adsorption of steroid hormones on the carbon nanotubes did not limit the hormones’ subsequent degradation. A report on their work has been published in Nature Communications (DOI: 10.1038/s41467-024-52730-7).
Researchers design a new way to more reliably evaluate AI models’ ability to make clinical decisions in realistic scenarios that closely mimic real-life interactions.
The analysis finds that large-language models excel at making diagnoses from exam-style questions but struggle to do so from conversational notes.
The researchers propose set of guidelines to optimize AI tools’ performance and align them with real-world practice before integrating them into the clinic.
A new international study led by researchers at Karolinska Institutet in Sweden shows that AI-based models can outperform human experts at identifying ovarian cancer in ultrasound images. The study is published in Nature Medicine.