Can AI save us from the arduous and time-consuming task of academic research collection? An international team of researchers investigated the credibility and efficiency of generative AI as an information-gathering tool in the medical field.

The research team, led by Professor Masaru Enomoto of the Graduate School of Medicine at Osaka Metropolitan University, fed identical clinical questions and literature selection criteria to two generative AIs; ChatGPT and Elicit.

Artificial intelligence (AI) may attempt to mimic the human brain, but it has yet to fully grasp the complexity of what it means to be human. While it may not truly understand feelings or original creativity, it can help us better understand ourselves - especially our physical bodies in health and in disease, according to a series of articles recently published by the journal Quantitative Biology.

Health care organizations are looking to artificial intelligence (AI) tools to improve patient care, but their translation into clinical settings has been inconsistent, in part because evaluating AI in health care remains challenging. In a new article, researchers propose a framework for using AI that includes practical guidance for applying values and that incorporates not just the tool's properties but the systems surrounding its use.

A team of researchers from LMU, ETH Zurich, and Roche Pharma Research and Early Development (pRED) Basel has used artificial intelligence (AI) to develop an innovative method that predicts the optimal method for synthesizing drug molecules. "This method has the potential to significantly reduce the number of required lab experiments, thereby increasing both the efficiency and sustainability of chemical synthesis,” says David Nippa, lead author of the corresponding paper, which has been published in the journal Nature Chemistry.

Researchers at UMC Utrecht have developed an AI model to predict long-term outcome in extremely premature babies early in life. The model can identify which infants might face intellectual disability as they grow. When further developed, it could offer crucial insights for healthcare providers as well as valuable information for parents about their child’s expected developmental journey.

Using a routine chest X-ray image, an artificial intelligence (AI) tool can identify non-smokers who are at high risk for lung cancer, according to a study being presented next week at the annual meeting of the Radiological Society of North America (RSNA).

Lung cancer is the most common cause of cancer death. The American Cancer Society estimates about 238,340 new cases of lung cancer in the United States this year and 127,070 lung cancer deaths.

A new artificial intelligence (AI) computer program created by researchers at the University of Florida and NVIDIA can generate doctors' notes so well that two physicians couldn't tell the difference, according to an early study from both groups.

In this proof-of-concept study, physicians reviewed patient notes - some written by actual medical doctors while others were created by the new AI program - and the physicians identified the correct author only 49% of the time.