Journal of Assisted Reproduction and Genetics - CALL FOR PAPERS
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Topical Collection title: Unlocking the potential of artificial intelligence (AI) in reproductive medicine: The JARG collection on assisted reproductive technology (ART) and machine learning
Guest Editors:
Carol Lynn Curchoe, Director of Medical Affairs at AIVF, USA
Gerard Letterie, Seattle Reproductive Medicine, USA
Alexander Quaas, Division Director of REI, University of Basel, Switzerland
Read the Guest Editors' Introductory Editorial here (this opens in a new tab)
Scope and call for manuscripts:
This collection of papers brings together the latest, cutting-edge research and delves into the promising role of Artificial Intelligence (AI) in shaping the future of reproductive medicine. With an aim to inspire and ignite innovation, this collection invites authors to contribute their own original and cutting-edge research, while providing readers with an exciting array of advancements in this rapidly evolving field.
Artificial intelligence surrounds us in daily living. But in an indirect, non-clinical and arm’s length way. And as such a devil-may-care attitude abides. If it works, who cares about details? (Most of us can't tell the difference between Python, Java, or C++ and frankly don’t care). It’s simply not part of the daily to-and-fro of delivering assisted reproductive technologies (ART). But evidence is mounting that AI can provide additional horsepower to the engine of decision making in ART. And this migration of AI into the front yard of clinical care should prompt us all to sit up, pay attention and take notes. Like it or not, AI has arrived on the ART scene. New AI tools are rapidly emerging in ART but without an easy-to-read user’s manual. As with all things new and novel, education is the foundation to make smart and well-informed decisions and avoid making premature grab-and-go choices in response to a hot topic pitch that we may live to regret.
As highlighted in this collection, the potential of AI in the reproductive space is spectacular, enabling more accurate predictions of pregnancy outcomes, optimized embryo selection, and personalized treatment plans based on individual characteristics and genetic profiles. Harnessing the power of AI, reproductive medicine is undergoing a paradigm shift, redefining the boundaries of what is possible. Machine learning algorithms have paved the way for improved diagnosis, treatment, and patient care. By leveraging vast amounts of data, AI systems can identify patterns, make predictions, and provide tailored recommendations to healthcare providers and patients.
However, as always, progress also comes with perils. Our field is ripe with examples of the principle “implementation before validation” where the enthusiasm for the utilization of new technologies exceeds the appreciation for potential pitfalls and risks. This phenomenon appears to be almost inevitable in the case of artificial intelligence (AI) assisted reproductive technology (ART). There is no longer any doubt regarding the integral role that AI will play in ART. While the “if” question regarding implementation is answered, we can still control the “how.” Are we outsourcing clinical care to a computer? How do AI tools impact the quintessentially clinical process that, until now, was solely within the purview of providers? Solid, high-quality prospective studies are needed to demonstrate improved outcomes and ideally, cost reduction. The crossroad between biology and informatics needs to be traversed by academics and experienced clinicians, as well as statistical experts, and guarded by solid peer review, rather than occupied entirely by commercial interests. Data integrity and safety are paramount. Furthermore, the care of our patients should continue to be holistic, empathetic, and not de-humanized. AI should not just provide fancy gadgets for to the privileged few, but advantages to the reproductive patient collective as a whole.
This collection showcases a wide range of papers that investigate the profound impact of AI on fertility-related topics, including assisted reproductive technologies, reproductive health monitoring, predictive modeling, and personalized medicine. By featuring a diverse range of interdisciplinary research, this collection serves as a platform for scientists, clinicians, and engineers to share their insights, innovations, and future visions. Through collaboration and knowledge exchange, we aspire to accelerate the progress of AI in reproductive medicine, ultimately improving outcomes for people struggling with infertility and reproductive health challenges.
Join us in this stimulating journey through the cutting-edge science of AI and fertility. Explore the remarkable breakthroughs, be inspired by the endless possibilities, and contribute your own original research to shape the future of reproductive medicine. Together, we can push the boundaries of science, technology, and human potential to revolutionize the field of fertility and bring hope to millions around the world. Read on and make your own decisions about how these new tools can positively impact what we do as individual practices and as a specialty. As we enter this new era, in awe of the rapid breakthroughs occurring in front of our eyes, we continue to remind ourselves of the ultimate goal of our work: healthy babies.
Submission Instructions
Before submitting your manuscript, please ensure you have carefully read the submission guidelines (this opens in a new tab). The complete manuscript should be submitted through the journal submission system. (this opens in a new tab)
The peer review process for articles included in this topical collection is the same as the peer review process of the journal in general. Additionally, if the Guest Editors author an article in their topical collection, they will not handle the peer review process.