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On this episode of Advances in Care, host Erin Welsh speaks with Dr. Zev Williams, Chief of the Division of Reproductive Endocrinology and Fertility at NewYork-Presbyterian and Columbia and Director of the Columbia University Fertility Center. Recently, Dr. Williams and a team of researchers and clinicians used artificial intelligence to develop a system called STAR, or Sperm Track and Recovery, which combines advanced imaging with innovations in microfluidic chip technology to more accurately identify and capture sperm in samples from patients with azoospermia – a condition that often leaves men with untraceable numbers of sperm in their semen.
Dr. Williams explains that some azoospermia patients might have two or three sperm cells as opposed to the typical two or three million and having human researchers looking for those cells under a microscope is painstaking and rarely leads to success. Inspired by the AI-powered technology that astrophysicists use to find stars, Dr. Williams and his colleagues set out to build a tool that could help embryologists not only find those few sperm in a field of cell debris, but also collect them gently for future fertilization in an expedited manner.
The effort took five years of research and development, along with a collaborative bench-to-bedside research approach that Dr. Williams says is unique to the Columbia University Fertility Center. But the work paid off, resulting in a successful pregnancy and a promising example of how AI will continue to transform reproductive medicine.
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Dr. Zev Williams is the Wendy D. Havens Associate Professor of Women's Health at Columbia and the Chief of the Division of Reproductive Endocrinology and Infertility at NewYork-Presbyterian Columbia University Irving Medical Center. As a physician scientist, Dr. Williams' focus has been on helping those suffering from recurrent pregnancy loss and infertility and developing novel technologies and treatments to improve patient success.
For more information visit nyp.org/Advances
By NewYork-Presbyterian4.9
4343 ratings
On this episode of Advances in Care, host Erin Welsh speaks with Dr. Zev Williams, Chief of the Division of Reproductive Endocrinology and Fertility at NewYork-Presbyterian and Columbia and Director of the Columbia University Fertility Center. Recently, Dr. Williams and a team of researchers and clinicians used artificial intelligence to develop a system called STAR, or Sperm Track and Recovery, which combines advanced imaging with innovations in microfluidic chip technology to more accurately identify and capture sperm in samples from patients with azoospermia – a condition that often leaves men with untraceable numbers of sperm in their semen.
Dr. Williams explains that some azoospermia patients might have two or three sperm cells as opposed to the typical two or three million and having human researchers looking for those cells under a microscope is painstaking and rarely leads to success. Inspired by the AI-powered technology that astrophysicists use to find stars, Dr. Williams and his colleagues set out to build a tool that could help embryologists not only find those few sperm in a field of cell debris, but also collect them gently for future fertilization in an expedited manner.
The effort took five years of research and development, along with a collaborative bench-to-bedside research approach that Dr. Williams says is unique to the Columbia University Fertility Center. But the work paid off, resulting in a successful pregnancy and a promising example of how AI will continue to transform reproductive medicine.
***
Dr. Zev Williams is the Wendy D. Havens Associate Professor of Women's Health at Columbia and the Chief of the Division of Reproductive Endocrinology and Infertility at NewYork-Presbyterian Columbia University Irving Medical Center. As a physician scientist, Dr. Williams' focus has been on helping those suffering from recurrent pregnancy loss and infertility and developing novel technologies and treatments to improve patient success.
For more information visit nyp.org/Advances

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