RESUMEN
Dependency on ChatGPT is characterized by excessive reliance on AI-driven conversational agents, such as ChatGPT, in the healthcare sector. This article explores the consequences of overreliance on AI chatbots like ChatGPT in healthcare settings. It discusses the increasing use of AI chatbots for patient consultations, information dissemination, and decision support, highlighting their potential benefits in improving healthcare delivery efficiency and patient outcomes. The editorial explores the factors contributing to ChatGPT Dependency Disorder among healthcare professionals, such as convenience, lack of training, and time constraints, and examines the challenges and benefits associated with integrating AI chatbots in clinical workflows. It emphasizes the importance of maintaining a human-centered approach alongside AI technologies to optimize patient care outcomes and emphasizes the need for responsible integration of AI chatbots in healthcare settings to ensure ethical standards and patient safety. This article concludes by calling for further research and strategies to address ChatGPT Dependency Disorder and promote a balanced approach to leveraging AI technology in healthcare practice.
RESUMEN
Google DeepMind Technologies Limited (London, United Kingdom) recently released its new version of the biomolecular structure predictor artificial intelligence (AI) model named AlphaFold 3. Superior in accuracy and more powerful than its predecessor AlphaFold 2, this innovation has astonished the world with its capacity and speed. It takes humans years to determine the structure of various proteins and how the shape works with the receptors but AlphaFold 3 predicts the same structure in seconds. The version's utility is unimaginable in the field of drug discoveries, vaccines, enzymatic processes, and determining the rate and effect of different biological processes. AlphaFold 3 uses similar machine learning and deep learning models such as Gemini (Google DeepMind Technologies Limited). AlphaFold 3 has already established itself as a turning point in the field of computational biochemistry and drug development along with receptor modulation and biomolecular development. With the help of AlphaFold 3 and models similar to this, researchers will gain unparalleled insights into the structural dynamics of proteins and their interactions, opening up new avenues for scientists and doctors to exploit for the benefit of the patient. The integration of AI models like AlphaFold 3, bolstered by rigorous validation against high-standard research publications, is set to catalyze further innovations and offer a glimpse into the future of biomedicine.