The document discusses the role of artificial intelligence (AI) in infertility care, highlighting its applications in reproductive medicine such as ovarian assessment and sperm analysis. It presents various case studies demonstrating the effectiveness of AI in tracking follicular growth and analyzing sperm parameters. The conclusion emphasizes the need for collaboration between AI developers and healthcare professionals to enhance IVF outcomes.

1. ARTIFICIAL INTELLIGENCE IN INFERTILITY
Prof. Dr. G. A. Rama Raju, Medical Director, Krishna IVF Clinic, Visakhapatnam

2. AI in Reproductive Medicine
Brief introduction to
AI, machine learning,
and predictive
models.
Overview of potential
applications of AI in
reproductive
medicine.
Discussion on the use
of AI in Assisted
Reproduction

3. EDWARD H SHORTLIFFE
• FIRST PERSON TO WRITE A PROGRAM FOR AI IN
MEDICINE
• MYCIN AN FROM STANFORD UNIVERSITY 1970

4. Rule based
expert system

5. Machine learning ?

6. AI in Reproductive Medicine
Ovary
Semen
analysis
Uterus
embryo
assessment

7. Automated detection and segmentation of follicle in 3d ultrasound

8. Segmentation and post processing

9. Case Study: AI in Ovarian Assessment

10. How to check AFC ?

11. USING SUPER RESOLUTION:
Super resolution

12. 5d follicle and Asrm Eshre guideline on PCO

13. Case Study: AI in
Longitudinal Follicular
Growth Tracking
•

14. Summary: Tracking follicles between days 1-4 is sufficient to
predict their size at
the end of cycle
Average Rate of Growth
(in mm/day)
Between days Inference
>1 1-4
Follicle will grow to
>10mm at end of cycle
0.6 – 1
(increasing)
1-4
Follicle will be between
4mm-10mm at the end
of cycle
0.6 – 0.1
(decreasing)
1-4
Follicle will have size
<4mm at end of cycle

15. Case Study: AI for
Follicle Tracking

17. longitudinal tracking of follicles in IVF cycles
Subject 1 Subject 2

18. Longitudinal analysis of follicular growth

19. Deep learning and unsupervised learning in follicle assement and
tracking

20. Discussion -
Interpretation in
context of literature
• This is a first of its kind attempt
to track spatial locations of
follicles in the ovary across IVF
cycles using blood vessels as
anatomical landmarks
• Earlier attempts have examined
tracking in normal cycles only
• We have attempted to study
follicular growth in an IVF
cycle
8/7/2023

21. Understanding the
Junctional Zone

22. Our work on
green journal

23. Predicting implantation success using junctional
zone assessment in assisted reproduction

24. Junctional zone and implantation

25. Junctional zone and cesarean section deliveries

26. Uterine
anomaly and
junction
zone

27. : AI in Sperm Analysis
Overview of the importance of sperm analysis in
infertility treatment.
Discussion on how AI can be used to analyse
sperm parameters more accurately and efficiently.
Presentation of any results or case studies you
have related to using AI in sperm analysis.

28. AI in Sperm Analysis

29. Progress of ai in semen analysis

30. AI in Time-Lapse
Embryo Monitoring
• Overview of the
importance of embryo
monitoring in IVF.
•

31. Embryo assessment

32. Time-lapse assessment

33. Morphokinetics events occurring during
fertilization
Combined. Data. To live birth Non-Implantation

34. Awards and
Recognition

35. Conclusion
• AI algorithms may help practitioners from around the globe to
standardize, automate, and improve IVF outcomes for the benefit of
patients. Collaboration is required between AI developers and
healthcare professionals to make this happen.