As a CEO of one of the fastest-growing femtech companies in the United States, I have witnessed firsthand how innovative technologies like artificial intelligence are empowering people on their reproductive journeys.
4 Fast Facts About Infertility
- Infertility means the inability to conceive after 12 months of regular and unprotected intercourse.
- About one in six people worldwide face infertility.
- In the United States, about one in four people, or 6.7 million individuals, have trouble conceiving each year.
- In approximately one-third of cases, infertility problems stem from a person’s reproductive health issues
By analyzing vast amounts of user data, AI algorithms offer personalized insights on treating a particular patient, and thus increasing the chances of successful fertility treatments. And, by accelerating decision-making processes, embryo selection and data analysis, AI can fix human error, the biggest challenge with in vitro fertilization (IVF).
Integrating advanced technologies into infertility treatment at clinics can enhance the effectiveness of such treatments while offering greater comfort for patients during this stressful period of their lives.
AI and At-Home Fertility Solutions
The global pandemic catalyzed the telehealth sector, with use of remote healthcare solutions increasing 29 percent among U.S. adults. Yet fertility care remains tied to brick-and-mortar facilities.
Moving fertility treatment out of traditional settings like the hospital will make the process more accessible and, ultimately, more cost-efficient. Adding remote hormone monitoring to fertility treatment protocols will allow patients to reduce clinic visits and blood draws by approximately 67 percent, according to Mira research.
In this hospital-to-homes transformation, technology plays a crucial role, especially AI-powered remote hormone monitoring, which is already being used in fertility testing and treatments, diagnosing women’s health conditions and other applications.
What Is At-Home Fertility Monitoring?
At-home fertility monitoring is AI-driven technology that tracks people’s hormones via daily tests for individual insights about their hormonal health and fertility status.
People can monitor their hormone levels by analyzing regular urine tests via mini at-home labs, with the results equally valid as those made in a lab.
By testing their hormones every day, people can see a clear picture of their hormonal health and get individual hormone insights, such as predicting ovulation and fertility windows, see a declining fertility pattern and the onset of perimenopause.
These accurate calculations are possible through AI-driven monitoring technology, trained on users’ hormone data points. This AI-based solution has the potential to replace traditional blood sampling by reducing the need for frequent clinic visits and minimizing testing costs.
Users feel more empowered when they know what is going on in their bodies. They also share accurate, real-time information about their hormones with their medical team.
Pluses and Minuses of AI-Powered Hormone Tracking
At-home monitoring is more affordable and also less painful, as it reduces the need for frequent blood draws.
Additionally, at-home monitoring gives a bigger picture than regular clinical blood tests. It reveals hormone patterns throughout many days of the cycle and over multiple months, rather than just twice per month, as blood tests allow. This holistic approach gives fertility specialists insights they have never had before, allowing them to tailor treatments in a much more individualized way.
As for possible disadvantages, health-care providers may recheck the test, as they often wish to see blood test results rather than urine testing. Also, all results should be interpreted cautiously, as they are just one piece of a larger picture.
How AI-Powered Hormone Tracking Boosts IVF Success
Regular hormonal tracking can increase the chances of IVF success. In a recent study conducted by Mira in partnership with Pelex, a fertility clinic, participants used a hormone tracking monitor to track their hormone cycles throughout the treatment.
As a result of the trial, 44 percent of participants got pregnant after two months of trying, while 72 percent received accurate diagnoses from regular at-home hormonal tracking. To compare, IVF success rate on the first try is about 40 percent.
By championing the adoption of remote monitoring and fostering collaboration between fertility tech and clinics, we can create a future where fertility care is more accessible, personalized and successful. The advancements in AI technology offer hope for patients, and the synergy between human expertise and cutting-edge algorithms can redefine the possibilities of reproductive health.
The continued rise and integration of AI, machine learning and remote patient monitoring in fertility care will further advance our understanding and treatment options. Integrating this data into a comprehensive global system of care can have a tangible impact on improving fertility rates and women’s health overall.
