# Generative AI in Medicine and Healthcare: Promises, Opportunities and Challenges
## 3 Current Efforts of Applying Generative AI and LLMs in Medicine and Healthcare
### Clinical Decision Support  
Given the advanced understanding of the human language and further fine-tuned domain knowledge, GPT models also have the potential to support clinical decision-making. Glass AI [25] is an LLM-powered experimental tool that offers clinical decision support. It serves as a diagnostic assistant to generate a list of possible diagnoses and treatment plans tailored to a clinical audience. For instance, when presented with a patient exhibiting symptoms such as fatigue, shortness of breath, and paleness, a provider can input these symptoms into Glass AI [26]. The system can then produce a comprehensive differential diagnosis, potentially suggesting conditions such as anemia, leukemia, or myelodysplastic syndromes. Additionally, Glass AI can assist in formulating a clinical plan, guiding the hematologist's next steps for further tests or treatment. Regard [27] is an AI tool integrated with EHR systems. By analyzing patient data, it suggests diagnoses, writes clinical notes, and provides relevant information quickly, optimizing patient care. It automates some EHR-related administrative tasks, enabling clinicians to focus more on patients and less on searching through screens. Regard's generative AI capabilities assist in the diagnostic process, generating a list of plausible and novel differential diagnoses based on patient data. This aids healthcare professionals (HCPs) in exploring different possibilities, confirming, or ruling out diagnoses, and optimizing treatment plans. For primary care physicians, hematologist-oncologists, dermatologists, and other specialists, Regard provides evidence-based suggestions, saving time and improving diagnostic specificity. As an intelligent co-pilot, Regard enhances HCPs' use of EHRs, promoting faster and more informed decision-making while emphasizing that it supports, rather than replaces, their clinical judgment and expertise. In pilot programs, Regard has demonstrated significant time-saving benefits and improved diagnostic accuracy for physicians. Redbrick AI's Fast Automated Segmentation Tool (F.A.S.T) [28] offers significant applications in medical imaging, assisting healthcare professionals in annotating and segmenting CT scans, MRI images, and ultrasounds. Redbrick AI provides a SaaS platform for annotating medical image data and offers F.A.S.T for use in radiology by utilizing Meta's Segment Anything model [29], presenting a possible solution for enhancing diagnostic accuracy and speed in healthcare. Its adaptive nature simplifies accurate segmentation without additional data, making it valuable for segmenting visible objects and features in radiology. The tool's real-time interaction allows clinicians to witness mask computation, streamlining segmentation. F.A.S.T. automates manual segmentation, enhancing diagnostic accuracy and speed in radiology. Paige FullFocus [30], fueled by generative AI, empowers HCPs to view, manage, and share digital slides of tissue samples, providing novel insights for treatment decisions and improving accuracy, efficiency, and diagnostic confidence. It excels in identifying and analyzing complex tissue patterns, aiding precise diagnoses in challenging cases like counting cancer cells in prostate and breast biopsies and identifying biomarkers for treatment selection. Additionally, FullFocus supports HCPs' clinical practice and education, enabling them to study diverse tissue patterns, expand their knowledge of hematological and oncological conditions, and stay updated with the latest pathology advancements. With FullFocus, HCPs can refine their diagnostic skills, deepen their expertise, and enhance patient care through continuous learning. The promising capability of Paige tools to provide more accurate tumor diagnosis was demonstrated in a prostate cancer research study conducted by [PERSON] et al. [31]. Kahun [32] is a symptom checker tool empowered by a conversational chatbot integrated with the EHR.