Routine Automated Assessment Using Surgical Intelligence Reveals Substantial Time Spent Outside the Patient's body in Minimally Invasive Gynecological Surgeries.

Levin, Ishai; Bar, Omri; Cohen, Aviad; Michaan, Nadav; Asselmann, Dotan; Wolf, Tamir

Levin, Ishai; Bar, Omri; Cohen, Aviad; Michaan, Nadav; Asselmann, Dotan; Wolf, Tamir.

Affiliation

Levin I; Department of Gynecology (Levin, Cohen, and Michaan), Lis Maternity Hospital, Tel Aviv Sourasky Medical Center Associated with Tel Aviv University, Tel Aviv, Israel. Electronic address: ishail@tlvmc.gov.il.
Bar O; Theator Inc. (Bar, Asselmann, and Wolf), Palo Alto, California.
Cohen A; Department of Gynecology (Levin, Cohen, and Michaan), Lis Maternity Hospital, Tel Aviv Sourasky Medical Center Associated with Tel Aviv University, Tel Aviv, Israel.
Michaan N; Department of Gynecology (Levin, Cohen, and Michaan), Lis Maternity Hospital, Tel Aviv Sourasky Medical Center Associated with Tel Aviv University, Tel Aviv, Israel.
Asselmann D; Theator Inc. (Bar, Asselmann, and Wolf), Palo Alto, California.
Wolf T; Theator Inc. (Bar, Asselmann, and Wolf), Palo Alto, California.

J Minim Invasive Gynecol ; 2024 Jun 06.

Article in En | MEDLINE | ID: mdl-38848990

Key words

Artificial intelligence; Computer vision; Minimally invasive gynecology; Visual obstacles in laparoscopy

Fulltext

Add to My VHL

XML

PubMed Links

Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Minim Invasive Gynecol Journal subject: GINECOLOGIA Year: 2024 Document type: Article Country of publication: Estados Unidos

Fulltext

Add to My VHL

XML

PubMed Links

Search on Google