Michelle Perugini - Concepedia

Author

Michelle Perugini

The University of Adelaide

Also Known As

M Perugini, M. Perugini, Michelle Perugini

Publications

1.2K

Citations

H-Index

Concepts

All Affiliations

The University of Adelaide South Australia Pathology Centre for Cancer Biology Ovation Fertility Texas Fertility Center

About

Michelle Perugini is an author at The University of Adelaide specializing in medicine, gene expression, and cell biology.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Medicine	5	5	191
2	Cell Biology	3	3	80
3	Immunology	2	2	57
4	Public Health	1	1	56
5	Biology	1	1	56

Michelle Perugini

Publications

863

Citations

H-Index

Page 1

	Year	Citations
Development of an artificial intelligence-based assessment model for prediction of embryo viability using static images captured by optical light microscopy during IVF Matthew VerMilyea, Jonathan M. M. Hall, Sonya M. Diakiw, Human Reproduction	2020	307
Dual epigenetic targeting with panobinostat and azacitidine in acute myeloid leukemia and high-risk myelodysplastic syndrome Puay Hoon Tan, Andrew H. Wei, Sridurga Mithraprabhu, Blood Cancer Journal	2014	95
Development of an artificial intelligence model for predicting the likelihood of human embryo euploidy based on blastocyst images from multiple imaging systems during IVF Sonya M. Diakiw, Jonathan M. M. Hall, Matthew VerMilyea, Human Reproduction	2022	89
Alternative modes of GM-CSF receptor activation revealed using activated mutants of the common β-subunit Michelle Perugini, Anna Brown, Diana Salerno, Blood	2010	67
A novel decentralized federated learning approach to train on globally distributed, poor quality, and protected private medical data Tuc Nguyen, M. Abou Dakka, Sonya M. Diakiw, Scientific Reports	2022	65
An artificial intelligence model correlated with morphological and genetic features of blastocyst quality improves ranking of viable embryos Sonya M. Diakiw, Jonathan M. M. Hall, Matthew VerMilyea, Reproductive BioMedicine Online BiologyInfertilityDevelopmental BiologyFertilityArtificial Intelligence Model	2022	56
A four-gene LincRNA expression signature predicts risk in multiple cohorts of acute myeloid leukemia patients Dominik Beck, Julie A.I. Thoms, Cintia Palu, Leukemia Hematological MalignancyMedicineGeneticsMixed-phenotype Acute LeukemiaGenetic Epidemiology	2017	55
The GM-CSF receptor utilizes β-catenin and Tcf4 to specify macrophage lineage differentiation Anna Brown, Diana Salerno, Teresa Sadras, Differentiation Cell LineageSignal TransductionSignaling PathwayMolecular PathwayImmunology	2011	32
Automated detection of poor-quality data: case studies in healthcare M. Abou Dakka, Tuc Nguyen, Jonathan M. M. Hall, Scientific Reports	2021	30
Nutlin-3a Efficacy in Sarcoma Predicted by Transcriptomic and Epigenetic Profiling Kathleen I. Pishas, Susan J. Neuhaus, Mark Clayer, Cancer Research Tp53 StatusNutlin-3a EfficacyMalignant DiseaseMedicineGene Expression	2013	25

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