An interpretable machine learning model for individualized gonadotrophin starting dose selection during ovarian stimulation.

Fanton, Michael; Nutting, Veronica; Rothman, Arielle; Maeder-York, Paxton; Hariton, Eduardo; Barash, Oleksii; Weckstein, Louis; Sakkas, Denny; Copperman, Alan B; Loewke, Kevin

Fanton, Michael; Nutting, Veronica; Rothman, Arielle; Maeder-York, Paxton; Hariton, Eduardo; Barash, Oleksii; Weckstein, Louis; Sakkas, Denny; Copperman, Alan B; Loewke, Kevin.

Affiliation

Fanton M; Alife Health, Inc., San Francisco CA, USA.
Nutting V; Alife Health, Inc., San Francisco CA, USA.
Rothman A; Alife Health, Inc., San Francisco CA, USA.
Maeder-York P; Alife Health, Inc., San Francisco CA, USA.
Hariton E; Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco CA, USA.
Barash O; Reproductive Science Center, San Ramon CA, USA.
Weckstein L; Reproductive Science Center, San Ramon CA, USA.
Sakkas D; Boston IVF - The Eugin Group, Waltham MA, USA.
Copperman AB; Reproductive Medicine Associates of New York, New York NY, USA.
Loewke K; Alife Health, Inc., San Francisco CA, USA. Electronic address: kloewke@alifehealth.com.

Reprod Biomed Online ; 45(6): 1152-1159, 2022 12.

Article in En | MEDLINE | ID: mdl-36096871

Subject(s)
Key words

Artificial intelligence; Gonadotrophins; IVF; Machine learning; Ovarian stimulation

Fulltext

Add to My VHL

XML

PubMed Links

Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Fertilization in Vitro / Sperm Injections, Intracytoplasmic Type of study: Observational_studies / Prognostic_studies Language: En Journal: Reprod Biomed Online Journal subject: MEDICINA REPRODUTIVA Year: 2022 Document type: Article Affiliation country: Estados Unidos Country of publication: Países Bajos

Fulltext

Add to My VHL

XML

PubMed Links

Search on Google