Generative Artificial Intelligence-Assisted Automated Image-Based Pneumonia Diagnosis

@article{1707509,
      author = {Frank Edughom Ekpar},
      title = {Generative Artificial Intelligence-Assisted Automated Image-Based Pneumonia Diagnosis},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {8},
      number = {9},
      pages = {717-728},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1707509.pdf},
      abstract = {Prompt engineering is leveraged to get generative artificial intelligence systems such as large language models to proffer steps for the development of a system for automated image-based diagnosis of pneumonia using two-dimensional convolutional neural networks. An initial prompt is utilized to get the large language model to divulge the general design of the system. The initial response of the generative artificial intelligence system is then followed up by a prompt that precipitates the generation of specific instructions and source code for the construction, training and testing of convolutional neural networks that are cognizant of the nature of the datasets employed. The trained artificial intelligence models could be adapted through refinements in robustness and performance for incorporation as automated image-based pneumonia detection modules into a comprehensive artificial intelligence-driven healthcare system.},
      keywords = {Pneumonia, Automated Pneumonia Diagnosis, Artificial Intelligence (AI), Deep Learning (DL), Artificial Neural Network (ANN), Convolutional Neural Network (CNN), Generative Artificial Intelligence, Large Language Model (LLM), ChatGPT, DeepSeek, TensorFlow, Healthcare System.},
      month = {March},
  }