Artificial Intelligence for Human Fertility: Trends, Insights, and Predictions

This book studies reasons behind the dramatic decline in total fertility rate (TFR), which has dropped to half of its previous levels. A major factor contributing to this trend is the widespread lack of recognition of fertility issues as a medical concern, compounded by insufficient societal awareness. To better understand the dynamics of human reproduction, this book identifies various factors that influence fertility, including the male and female reproductive systems, lifestyle choices, career demands, societal pressures, environmental factors, and personal habits (e.g., millennials). Central to this understanding is the collection of vast amounts of data, for which AI algorithms play a crucial role. The book studies how AI can help predict fertility outcomes by analyzing diverse datasets for both male and female populations. It also discusses the growing reliance on assisted reproductive technologies, despite their high costs and inconsistent success rates, and how AI can assist in predicting these success rates to ease the financial burden on patients. The primary goal of this book is to highlight how (explainable) AI can become a powerful tool in predicting human fertility. Ultimately, it aims at raising the global TFR and addressing the challenges posed by declining fertility rates around the world.

Studies reasons behind the dramatic decline in total fertility rate (TFR) Considers how AI can help predict fertility outcomes by analyzing diverse datasets for both male and female populations Highlights how (explainable) AI can become a powerful tool in predicting human fertility

Autorentext

Prof. KC Santosh-a highly accomplished AI expert-is the chair of the Department of Computer Science and the founding director of the Applied AI Research Lab at the University of South Dakota. He is also served the National Institutes of Health as a research fellow and LORIA Research Center as a postdoctoral research scientist, in collaboration with industrial partner, ITESOFT, France. He earned his Ph.D. in Computer Science-Artificial Intelligence from INRIA Nancy Grand East Research Center (France). With funding exceeding $2 million from sources like DOD, NSF, and SDBOR, he has authored 10 books and over 250 peer-reviewed research articles, including IEEE TPAMI. He serves as an associate editor for esteemed journals such as IEEE Transactions on AI, Int. J of Machine Learning & Cybernetics, and Int. J of Pattern Recognition & Artificial Intelligence. He, founder of AI programs at USD, has significantly boosted graduate enrollment by over 3,000% in just three years, establishing USD as a leader in AI within South Dakota. Dr. Rodrigue Rizk is an assistant professor at the University of South Dakota, holding a B.E. degree in computer and communication engineering with Summa Cum Laude highest honor distinction from Notre Dame University. He earned both his M.S. and Ph.D. degrees in Computer Engineering from the University of Louisiana at Lafayette, maintaining 4.0 GPA. Specializing in the dynamic interplay between software and hardware, his research interests span high-level computational systems, artificial intelligence, quantum computing, and more. He is a licensed professional engineer, a member of the Order of the Engineer, and holds various accolades, including the Richard G. and Mary B. Neiheisel endowed fellowship. He is a lifetime member of the Phi Kappa Phi honor society and a professional member of ACM and IEEE. His contributions have earned him numerous awards, including the President's Award for Educational Excellence and Outstanding Academic Achievement. Mr. Siddhi K Bajracharya is a research fellow for the Applied AI Research Lab, Department of Computer Science at the University of South Dakota. His research study focuses on building generic and/or generalized machine learning models for multiple data types: numbers, texts, and images.

Klappentext

Human Fertility and Global Trends.- Analysis of Human Reproductive Dynamics.- Leveraging AI and Fundamentals.- XAI: Healthcare focusing on fertility assessment.- Summary and Take-home Notes.

Inhalt

Human Fertility and Global Trends.- Analysis of Human Reproductive Dynamics.- Leveraging AI and Fundamentals.- XAI: Healthcare focusing on fertility assessment.- Summary and Take-home Notes.