Results 171 to 180 of about 74,936 (290)

Advancing clinical utility of artificial intelligence: lessons from developing a model to predict cochlear implant eligibility. [PDF]

JAMIA Open
Carducci V, Sanchez-Trigo H, Elgabori Y, Carlson M, Deep N, Romero-Brufau S.   +5 more
europepmc   +1 more source

A DNA methylation assay (MPap) using self‐collected tampon versus cytology collection swab for endometrial cancer detection

International Journal of Gynecology &Obstetrics, EarlyView.
Abstract Objective To evaluate the practicability of self‐collected tampons with the MPap assay for endometrial cancer (EC) detection, by comparing with the results of cervical swabs. Methods A total of 85 women at Tri‐Service General Hospital (TSGH) were included to directly compare the performance of physician‐collected swabs and self‐collected ...
Kuo‐Min Su, Kuo‐Chang Wen, Yi‐Hsin Lin, Po‐Hsuan Su, Lin‐Yu Chen, Hung Cheng Lai   +5 more
wiley   +1 more source

CT image-based machine learning models for predicting blood eosinophil levels in acute exacerbation of chronic obstructive pulmonary disease. [PDF]

BMC Pulm Med
Zhao S, Wu Y, Du L, Jia H, Monkam P, Qian W, Wang R, Xia S, Qi S.   +8 more
europepmc   +1 more source

Exploring Disordered Morphologies of Blends and Block Copolymers for Light-Emitting Diodes with Mesoscopic Simulations

, 2020
Daoulas, K., Kremer, K., Michels, J., Zhang, J.   +3 more
core   +1 more source

Machine learning‐based prediction of large‐for‐gestational‐age neonates in diabetic and non‐diabetic pregnancies

International Journal of Gynecology &Obstetrics, EarlyView.
Abstract Objective This study determines whether a machine‐learning model integrating sonographic biometry with maternal clinical parameters improves prediction of large‐for‐gestational‐age (LGA) compared with Hadlock's EFW formula. Methods We conducted a retrospective cohort study including all singleton live births at ≥32 gestational weeks at a ...
Ohad Houri, Asaf Romano, Asnat Walfisch, Eran Hadar, Yinon Gilboa, Leor Perl, Nadav Loebl, Ron Unger   +7 more
wiley   +1 more source

Comparison of the Hypotension Prediction Index and pulse pressure variation-guided haemodynamic management for intra-operative hypotension during kidney transplant: A randomised controlled trial. [PDF]

Indian J Anaesth
Aditya AS, Kajal K, Sethi S, Premkumar M, Naik N, Sharma A.   +5 more
europepmc   +1 more source

Neutrophil‐to‐lymphocyte ratio at admission helps to predict the need for blood transfusion after vaginal delivery

International Journal of Gynecology &Obstetrics, EarlyView.
Abstract Objective This study assesses the association between complete blood count (CBC) parameters, including the neutrophil‐to‐lymphocyte ratio (NLR) and the platelet‐to‐lymphocyte ratio (PLR) and predicts the need for postpartum packed red blood cell transfusion (pRBCT).
Daniel Gabbai, Itamar Gilboa, Anat Lavie, Yariv Yogev, Emmanuel Attali   +4 more
wiley   +1 more source

Improving prediction of ypT0-1N0 response in rectal cancer: the added value of gross tumor type to magnetic resonance tumor regression grade after chemoradiotherapy in a retrospective cohort study. [PDF]

Ann Surg Treat Res
Kang KM, Choi MJ, Ahn HM, Oh HK, Kim DW, Cho J, Chang W, Kim YH, Lee KH, Jun YK, Choi Y, Kang SB.   +11 more
europepmc   +1 more source

Hematologic markers and machine learning in predicting placenta accreta: A case–control study

International Journal of Gynecology &Obstetrics, EarlyView.
Abstract Objective This study aims to enhance antenatal detection of placenta accreta spectrum (PAS) and predict severe hemorrhage at delivery using machine learning by evaluating the association between antenatal hematologic index trends across trimesters, imaging markers, and patient history.
Michael D. Jochum, Kelly D. Albrecht, Yamely Mendez Martinez, Victoria Zhang, Sanmay Sarada, Brian Burnett, Christina C. Reed, Karin A. Fox, Amir A. Shamshirsaz, Michael A. Belfort, Jessian L. Munoz, Hennie A. Lombaard   +11 more
wiley   +1 more source

Enhanced cricket match prediction using kernel methods for feature extraction and back-propagation neural networks. [PDF]

Sci Rep
Dhinakaran K, Anbuchelian S.
europepmc   +1 more source