Unveiling large multimodal models in pulmonary CT: A comparative assessment of generative AI performance in lung cancer diagnostics
Peer-Reviewed Publication
Updates every hour. Last Updated: 23-Jan-2026 16:11 ET (23-Jan-2026 21:11 GMT/UTC)
The objective of this study is to assess the diagnostic performance of image analysis-capable generative AI (Gen-AI) (GPT-4-turbo, Google DeepMind's Gemini-pro-vision, and Anthropic’s Claude-3-opus) in interpreting CT images of lung cancer. This is the first study to integrate the diagnostic capabilities of these three models across distinct imaging settings. Additionally, a Likert scale is used to evaluate each model's internal tendencies. By examining the potential and limitations of multimodal large language models (MM-LLMs) for lung cancer diagnosis, this research aims to provide an evidence-based foundation for the future clinical applications of Gen-AI.
A holistic approach reveals the global spectrum of knowledge on the impact of cumulative heat exposure on young students, according to an article published July 30 in the open-access journal PLOS Climate by Konstantina Vasilakopoulou from the Royal Melbourne Institute of Technology, Australia, and Matthaios Santamouris from the University of New South Wales, Australia. The article aims to shed light on the social and economic inequalities caused within and across countries, the potential adaptive measures to counterbalance the impact of overheating, and forecasts about the cognitive risks associated with future overheating.
Researchers have demonstrated a new tool to improve the security of small-scale business transactions with the goal of helping ensure that businesses are paid and customers get what they pay for. The tool, which relies on blockchain-powered smart contracts, essentially serves the same function that letters of credit provide for large companies.
The American Association for the Advancement of Science (AAAS) is pleased to announce its partnership with the China Civil Engineering Society (CCES) and Tsinghua University (THU) to publish Civil Engineering Sciences as a Science Partner Journal.