IVF And Artificial Intelligence, A Match For Making Babies

In Vitro Fertilization (IVF), first successfully performed in 1978, has helped in the birth of over eight million babies since its inception. However, the process is by no means easy, with a current success rate of only 29% for women under 35, and 2% for women over 44.

In an attempt to better the odds, many AI companies have been working to develop software to aid in the IVF process. Alife is one of these companies, recently raising $9.5 million in seed funding to begin expanding its AI platform.

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The new software being manufactured will combine data from hundreds of thousands of patients worldwide and, using machine learning, convey statistics and patterns in outcomes to physicians and patients in an attempt to provide the best recommendations for treatment. This technology will not replace the clinical judgement of doctors, but rather would create data analysis features to serve as an aid in finding the best patient solutions.

What would previously take countless hours of physician research and case study, can now be achieved in mere minutes, and from angles that physicians may not usually see or pursue. The hope is that the utilization of AI in this case can increase the number of successful outcomes.

Alife is not the only company trying to expand in this field. Many AI software firms and development companies are looking for ways to revolutionize IVF administration. Embryonics, for instance, uses the anonymized patient records of millions to contribute to IVF decision making. Presagen, an AI start-up specializing in improving women’s healthcare, recently launched Life Whisper, which analyzes the likelihood of embryo success by using AI to analyze 2D imagery.

Even large pharmaceutical companies have taken interest in IVF, with Philips and Merck partnering last year to create an AI-enabled ultrasound service and personalized fertility treatment that is cloud-based and can be administered remotely.

IVF is set to see some big changes in the coming years as a result of AI implementation in the treatment processes. Rates of success may continue to rise with new identification methods and millions of data files being compiled into one convenient place thanks to artificial intelligence.