The research team behind the study published on Wednesday, July 3, in the journal PLOS ONE, took on the serious task of comparing participants’ reactions to jokes written by ChatGPT 3.5 and others written by people.
Researchers from the Wellcome Sanger Institute, University of the Witwatersrand and National Institute for Communicable Diseases in South Africa, the University of Cambridge, and partners across the Global Pneumococcal Sequencing project, integrated genomic data from nearly 7,000 Streptococcus pneumoniae (pneumococcus) samples collected in South Africa with detailed human mobility data.
DeepPT, developed in collaboration with scientists at the National Cancer Institute in America and pharmaceutical company Pangea Biomed, works by predicting a patient's messenger RNA (mRNA) profile.
Tulane University researchers made progress toward that vision by developing a new deep learning algorithm that outperformed existing computer-based osteoporosis risk prediction methods, potentially leading to earlier diagnoses and better outcomes for patients with osteoporosis risk.
These models have also been shown to develop some surprising abilities.
However, predicting which proteins bind together has been a challenging aspect of computational biology, primarily due to the vast diversity and complexity of protein structures.
Unlike other robots in this space, CARMEN was developed by the research team at the University of California San Diego in collaboration with clinicians, people with MCI, and their care partners.