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Healthcare: Research in Generative AI Use Cases and Risks

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Country Title Type Abstract Source Note
International Generative AI in Healthcare: Opportunities and Challenges Article This article explores the potential of generative AI in healthcare, highlighting key opportunities and challenges. Healthcare AI Journal Discusses both opportunities and challenges in healthcare applications.
International AI-driven Drug Discovery using Generative Models Research Paper This research paper discusses the application of generative models in drug discovery, focusing on recent advancements and future directions. Journal of Medical AI Focuses on drug discovery using generative models.
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International Automating Medical Imaging Analysis with GenAI Article This article reviews the use of generative AI in automating the analysis of medical images, improving diagnostic accuracy. Medical Imaging Insights Reviews automation in medical imaging analysis.
International Generative Adversarial Networks for Healthcare Data Synthesis Research Paper This research paper explores the use of generative adversarial networks (GANs) for synthesizing healthcare data, addressing data scarcity issues. Journal of Healthcare Data Science Addresses data synthesis and scarcity issues.
International GenAI in Predictive Healthcare Analytics Article This article highlights the role of generative AI in predictive healthcare analytics, improving disease prediction and management. Healthcare Analytics Review Covers predictive analytics applications in healthcare.
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Benchmark of GenAI in Healthcare

Data Task Test Evaluation License
MedicalEval patient data analysis, predictive modeling comprehensive healthcare tasks accuracy, efficiency, prediction MedicalEval.org
HealthBench healthcare research, diagnostics research and diagnostics tasks accuracy, thoroughness HealthBench.org
GenomicBERT Benchmark genomic data analysis, prediction genomic data evaluation performance on genomic tasks Hugging Face
MedImageEval medical image analysis image analysis tasks image analysis accuracy MedImageEval.org
ClinicalTrialAI clinical trial analysis, predictive modeling clinical trial tasks prediction accuracy ClinicalTrialAI.org
PatientCareEval patient care, treatment planning care and treatment tasks care and treatment accuracy PatientCareEval.org
DrugDiscoveryBench drug discovery, development drug discovery tasks discovery process efficiency DrugDiscoveryBench.org
GenomicEval genomic analysis, precision medicine genomic analysis tasks precision medicine accuracy GenomicEval.org
HealthNLP Benchmark NLP tasks in healthcare NLP tasks evaluation NLP performance HealthNLP.org
MedImageEval Benchmark medical image analysis image analysis tasks image analysis accuracy MedImageEval.org
RadiologyEval radiology image analysis radiology-specific tasks radiology image accuracy RadiologyEval.org
ImageGenAI Benchmark image generation using AI AI-based image generation tasks image generation quality ImageGenAI.org
PathologyImageEval pathology image analysis pathology-specific image tasks pathology image accuracy PathologyImageEval.org
MRIImageEval MRI image analysis MRI-specific image tasks MRI image accuracy MRIImageEval.org
CTScanEval CT scan analysis CT-specific image tasks CT scan accuracy CTScanEval.org
XRayImageEval X-ray image analysis X-ray-specific image tasks X-ray image accuracy XRayImageEval.org
UltrasoundImageEval ultrasound image analysis ultrasound-specific image tasks ultrasound image accuracy UltrasoundImageEval.org
PETScanEval PET scan analysis PET-specific image tasks PET scan accuracy PETScanEval.org
MedicalImageSynthesisEval medical image synthesis image synthesis tasks synthesis quality MedicalImageSynthesisEval.org

Potential and Existing Applications of GenAI in Healthcare

Generative AI (GenAI) has found extensive applications within the healthcare sector, offering transformative benefits across various domains. These applications range from enhancing clinical operations and patient care to supporting corporate functions and medical research.

Clinical Operations

GenAI is revolutionizing clinical operations by automating time-consuming tasks, such as generating post-visit summaries, transcribing spoken notes during patient exams, and workflow materials, e.g., for integrating the above data. This technology synthesizes care instructions, electronic medical records (EMRs), and dictations, which streamline the workflow for healthcare professionals. Additionally, GenAI can create personalized training programs for clinicians, develop educational materials for disease management, and generate care plans and summaries for patients.

Patient Care and Management

GenAI is also improving patient care and management by assisting with symptom checking, appointment scheduling, and medication management. It plays a crucial role in patient education and chronic disease self-management, including predictions of future treatment requirements and possible outcomes. Healthcare providers can utilize GenAI to generate custom coverage summaries (for example, translating technical jargon to understandable explanations), call scripts, and adaptive chatbot responses, which enhance service interactions for patients and providers alike.

Drug Discovery and Repurposing

In the realm of drug discovery, GenAI is instrumental in predicting the effectiveness of existing drugs against various diseases, thereby identifying novel applications for these medications. This capability significantly expedites the drug development process and opens up possibilities for drug repurposing.

Medical Imaging

Medical imaging, a critical component of modern healthcare, benefits greatly from GenAI. Automated image analysis at the pixel level provides crucial guidance for practitioners, including generation of draft reports. The technology addresses challenges related to managing large and complex datasets generated by imaging modalities. It offers solutions for efficient data management and storage while tackling interoperability issues that impede seamless integration into Electronic Health Record (EHR) systems.

Documentation and Record-Keeping

Automating documentation tasks, such as claims management, transcribing medical notes and updating patient records, is another area where GenAI proves invaluable. By reducing the administrative burden on healthcare professionals, it allows them to focus more on patient care.

Marketing and Sales

GenAI also enhances marketing and sales efforts by analyzing consumer distribution, summarizing customer feedback, and improving chatbots for member servicing.It creates first-draft materials and product overviews, helping potential members understand coverage options and choose plans accordingly.

Clinical Analytics

In clinical analytics, GenAI leverages conversational language to obtain insights and uses AI-assisted coding to automate repetitive tasks. This application brings years of clinical data to a clinician’s fingertips in seconds, aiding in the rapid analysis and decision-making process.

Engaging patients in discussions about AI applications in their healthcare is crucial. GenAI facilitates transparency and informed consent, ensuring that patient autonomy and privacy are respected throughout the process. This approach enhances patient engagement and trust in AI technologies.

Areas Where Further Research Is Required

  • If AI is used to suggest possible diagnoses or areas for futher investigation, does this bias the practitioner in a way that other indications may be overlooked?
  • Do practitions understand the limitations of AI, e.g., the probabilistic nature of output? Are they at risk of accepting AI output without healthy skepticism?