About this Research Topic
Allergology, the study of allergies and immune system disorders, has witnessed remarkable advancements over the past few decades. However, the recent incorporation of Artificial Intelligence (AI) into the field is revolutionizing diagnostic and treatment paradigms, promising rapid, effective, and personalized patient care. While AI holds potential opportunities, from enhanced screening processes to customized management approaches, it also presents challenges related to accuracy, ethics, and the potential for over-reliance on technology in a field deeply rooted in patient-clinician interactions.
This Research Topic aims to address the critical and emerging intersection of Artificial Intelligence (AI) applications within the field of Allergology. The primary problem centres around discerning the optimal ways to adapt AI for patient screening, accurate diagnosis, and personalized management of allergies, while simultaneously navigating the potential risks and pitfalls such as data privacy, model accuracy, and over-reliance on technology. Through this investigation, we seek to foster a balanced dialogue between technology developers and medical professionals, aiming for innovations that are both ground-breaking and ethically sound, ultimately enhancing patient care in allergy practice.
Contributors are encouraged to explore and address the following sub-themes within the broad intersection of Artificial Intelligence and Allergology:
• Tracing the development and integration of AI within Allergology and its impact on patient care.
• Evaluating current and potential AI-driven tools and methodologies for early and accurate detection of allergic conditions.
• Investigating AI's role in customizing individualized treatment plans based on genetic, environmental, and clinical data.
• The ethical implications of AI in medicine, with a focus on data privacy, consent, and the human touch in allergology care.
• Scrutinizing the reliability and accuracy of AI models in diagnosing and predicting allergic reactions, comparing them against traditional methods.
• Assessing the cost implications of integrating AI into allergy practice and its potential to make quality care more accessible to diverse populations.
• Emphasizing the importance of fostering dialogue between technologists, clinicians, and patients to ensure AI's sustainable and beneficial growth in the field.
• Identifying potential pitfalls, challenges, and roadblocks in the widespread adoption of AI in Allergology and strategies to mitigate them.
• Speculating on the future of AI within Allergology, potential breakthroughs, and what the next decade might look like.
All article types accepted by Frontiers are encouraged.
This Research Topic aims to address the critical and emerging intersection of Artificial Intelligence (AI) applications within the field of Allergology. The primary problem centres around discerning the optimal ways to adapt AI for patient screening, accurate diagnosis, and personalized management of allergies, while simultaneously navigating the potential risks and pitfalls such as data privacy, model accuracy, and over-reliance on technology. Through this investigation, we seek to foster a balanced dialogue between technology developers and medical professionals, aiming for innovations that are both ground-breaking and ethically sound, ultimately enhancing patient care in allergy practice.
Contributors are encouraged to explore and address the following sub-themes within the broad intersection of Artificial Intelligence and Allergology:
• Tracing the development and integration of AI within Allergology and its impact on patient care.
• Evaluating current and potential AI-driven tools and methodologies for early and accurate detection of allergic conditions.
• Investigating AI's role in customizing individualized treatment plans based on genetic, environmental, and clinical data.
• The ethical implications of AI in medicine, with a focus on data privacy, consent, and the human touch in allergology care.
• Scrutinizing the reliability and accuracy of AI models in diagnosing and predicting allergic reactions, comparing them against traditional methods.
• Assessing the cost implications of integrating AI into allergy practice and its potential to make quality care more accessible to diverse populations.
• Emphasizing the importance of fostering dialogue between technologists, clinicians, and patients to ensure AI's sustainable and beneficial growth in the field.
• Identifying potential pitfalls, challenges, and roadblocks in the widespread adoption of AI in Allergology and strategies to mitigate them.
• Speculating on the future of AI within Allergology, potential breakthroughs, and what the next decade might look like.
All article types accepted by Frontiers are encouraged.
Keywords: Allergology, Artificial intelligence, Chatbot, Data privacy, Diagnostic technologies, Healthcare, Personalized medicine.
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
