About
In Vitro Fertilization (IVF) is a groundbreaking assisted reproductive technology that involves fertilizing an egg outside the human body and implanting the resulting embryo into the uterus. This field is crucial for individuals and couples facing infertility, offering a solution for those struggling to conceive naturally. Researchers in IVF focus on optimizing the techniques involved in egg retrieval, embryo culture, and implantation to increase success rates and ensure healthy pregnancies.
The study of IVF integrates insights from embryology, reproductive medicine, and genetics to enhance the understanding of fertility and improve clinical outcomes. By exploring areas such as embryo selection, cryopreservation, and preimplantation genetic testing, research in IVF aims to refine procedures and address challenges related to fertility treatments. Advancements in this field are essential for enhancing reproductive health, expanding treatment options, and fulfilling the dream of parenthood for countless individuals.
Why publish with us?
Global Visibility – Indexed in major databases
Fast Peer Review – Decision within 14–21 days
Open Access – Maximize readership and citation
Multidisciplinary Scope – Biology, Medicine and Engineering
Editorial Board Excellence – Global experts involved
University Library Indexing – Via OCLC
Permanent Archiving – CrossRef DOI
APC – Affordable APCs with discounts
Citation – High Citation Potential
Which articles are now trending?
Research Articles
- Technical & Economic Feasibility Study of Proposed Pump Storage Power Plants at Kuda Oya, Mul Oya, Gurugal Oya, and Dambagasthalawa
- Synergistic Assessment of Supplementation of Ascorbic Acid and Massularia acuminata Extracts on Serum Electrolyte and Lipid Profile Indices of Dyslipidemia in Adult Wistar Rats Exposed to Aluminum Chloride Toxicity
- Microgravity Employment in Archaeology – Available Experience and Future Perspectives
- Solar Energy Resource Potentials of the City of Arkadag
- Enhancing Material Property Predictions through Optimized KNN Imputation and Deep Neural Network Modeling
- Investigation and Energy Modeling of New Generation Environmentally Friendly Energy Source Thorium Fueled Molten Salt Reactors
Advertisement


