Výsledky vyhledávání - "Rohan Pooniwala"

Akademický článek

Evaluation of deep convolutional neural networks in classifying human embryo images based on their morphological quality

Autor: Prudhvi Thirumalaraju, Manoj Kumar Kanakasabapathy, Charles L. Bormann, Raghav Gupta, Rohan Pooniwala, Hemanth Kandula, Irene Souter, Irene Dimitriadis, Hadi Shafiee

Publikováno v: Heliyon, Vol 7, Iss 2, Pp e06298- (2021)

A critical factor that influences the success of an in-vitro fertilization (IVF) treatment cycle is the quality of the transferred embryo. Embryo morphology assessments, conventionally performed through manual microscopic analysis suffer from dispari

Externí odkaz: https://doaj.org/article/e32835dd1972430db11be2667016ce94

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Akademický článek

Performance of a deep learning based neural network in the selection of human blastocysts for implantation

Autor: Charles L Bormann, Manoj Kumar Kanakasabapathy, Prudhvi Thirumalaraju, Raghav Gupta, Rohan Pooniwala, Hemanth Kandula, Eduardo Hariton, Irene Souter, Irene Dimitriadis, Leslie B Ramirez, Carol L Curchoe, Jason Swain, Lynn M Boehnlein, Hadi Shafiee

Publikováno v: eLife, Vol 9 (2020)

Deep learning in in vitro fertilization is currently being evaluated in the development of assistive tools for the determination of transfer order and implantation potential using time-lapse data collected through expensive imaging hardware. Assistiv

Externí odkaz: https://doaj.org/article/8c0c11ce9b714029ab17cfb7a3360828

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Adaptive adversarial neural networks for the analysis of lossy and domain-shifted datasets of medical images

Autor: Anjali Devi Sivakumar, Fenil Doshi, Athe M. N. Tsibris, Deeksha Kartik, John C. Petrozza, Hadi Shafiee, Manoj Kumar Kanakasabapathy, John A. Branda, Charles L. Bormann, Rohan Pooniwala, Raghav Gupta, Prudhvi Thirumalaraju, Hemanth Kandula, Daniel R. Kuritzkes

Publikováno v: Nat Biomed Eng

In machine learning for image-based medical diagnostics, supervised convolutional neural networks are typically trained with large and expertly annotated datasets obtained using high-resolution imaging systems. Moreover, the network’s performance c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::50824745ccc3e9166cbc3d127e586ac5
https://doi.org/10.1038/s41551-021-00733-w

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Development and evaluation of inexpensive automated deep learning-based imaging systems for embryology

Autor: Raghav Gupta, Hemanth Kandula, Sandeep Kota Sai Pavan, Manoj Kumar Kanakasabapathy, Prudhvi Thirumalaraju, Irene Souter, Rohan Pooniwala, Irene Dimitriadis, Hadi Shafiee, V. Yogesh, Divyank Yarravarapu, Charles L. Bormann

Publikováno v: Lab Chip

Embryo assessment and selection is a critical step in an In-vitro fertilization (IVF) procedure. Current embryo assessment approaches such as manual microscopic analysis done by embryologists or semi-automated time-lapse imaging systems are highly su

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::73cc0b02550e1bb3d5e04308a09dde3c
https://doi.org/10.1039/c9lc00721k

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Deep learning early warning system for embryo culture conditions and embryologist performance in the ART laboratory

Autor: Raghav Gupta, Carol Lynn Curchoe, Charles L. Bormann, Hemanth Kandula, Hadi Shafiee, Rohan Pooniwala, Irene Souter, Prudhvi Thirumalaraju, Irene Dimitriadis, Manoj Kumar Kanakasabapathy

Publikováno v: J Assist Reprod Genet

Staff competency is a crucial component of the in vitro fertilization (IVF) laboratory quality management system because it impacts clinical outcomes and informs the key performance indicators (KPIs) used to continuously monitor and assess culture co

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4ea96f97ffa089347f50ba355dfb5414
https://pubmed.ncbi.nlm.nih.gov/33990900

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Evaluation of deep convolutional neural networks in classifying human embryo images based on their morphological quality

Autor: Rohan Pooniwala, Hadi Shafiee, Raghav Gupta, Prudhvi Thirumalaraju, Hemanth Kandula, Irene Dimitriadis, Manoj Kumar Kanakasabapathy, Irene Souter, Charles L. Bormann

Publikováno v: Heliyon
Heliyon, Vol 7, Iss 2, Pp e06298-(2021)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::21a974fa60cc50a4578740f8ce9cddd5
https://pubmed.ncbi.nlm.nih.gov/33665450

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Consistency and objectivity of automated embryo assessments using deep neural networks

Autor: Raghav Gupta, Prudhvi Thirumalaraju, Irene Dimitriadis, Charles L. Bormann, Rohan Pooniwala, Hadi Shafiee, Hemanth Kandula, Manoj Kumar Kanakasabapathy, Irene Souter

Publikováno v: Fertility and sterility

Objective To evaluate the consistency and objectivity of deep neural networks in embryo scoring and making disposition decisions for biopsy and cryopreservation in comparison to grading by highly trained embryologists. Design Prospective double-blind

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e30d377734232c71522fe51ca57ab918
http://europepmc.org/articles/PMC7583085

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