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Search life-sciences literature (45,100,050 articles, preprints and more)

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Empowering Data Sharing in Neuroscience: A Deep Learning De-identification Method for Pediatric Brain MRIs.
Familiar AM, Khalili N, Khalili N, Schuman C, Grove E, Viswanathan K, Seidlitz J, Alexander-Bloch A, Zapaishchykova A, Kann BH, Vossough A, Storm PB, Resnick AC, Kazerooni AF, Nabavizadeh A
AJNR Am J Neuroradiol, ajnr.A8581, 12 Nov 2024
Cited by: 0 articles | PMID: 39532533
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Sex-Specific Differences in Patients with <i>IDH1</i>-Wild-Type Grade 4 Glioma in the ReSPOND Consortium.
Gongala S, Garcia JA, Korakavi N, Patil N, Akbari H, Sloan A, Barnholtz-Sloan JS, Sun J, Griffith B, Poisson LM, Booth TC, Jain R, Mohan S, Nasralla MP, Bakas S, Tippareddy C, Puig J, Palmer JD, Shi W, [...] ReSPOND Consortium
AJNR Am J Neuroradiol, 45(9):1299-1307, 09 Sep 2024
Cited by: 1 article | PMID: 38684319
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A multi-institutional meningioma MRI dataset for automated multi-sequence image segmentation.
LaBella D, Khanna O, McBurney-Lin S, Mclean R, Nedelec P, Rashid AS, Tahon NH, Altes T, Baid U, Bhalerao R, Dhemesh Y, Floyd S, Godfrey D, Hilal F, Janas A, Kazerooni A, Kent C, Kirkpatrick J, Kofler F, [...] Calabrese E
Sci Data, 11(1):496, 15 May 2024
Cited by: 2 articles | PMID: 38750041 | PMCID: PMC11096318
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Active Learning in Brain Tumor Segmentation with Uncertainty Sampling and Annotation Redundancy Restriction.
Kim DD, Chandra RS, Yang L, Wu J, Feng X, Atalay M, Bettegowda C, Jones C, Sair H, Liao WH, Zhu C, Zou B, Kazerooni AF, Nabavizadeh A, Jiao Z, Peng J, Bai HX
J Imaging Inform Med, 37(5):2099-2107, 21 Mar 2024
Cited by: 1 article | PMID: 38514595 | PMCID: PMC11522245
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Multiparametric MRI Along with Machine Learning Informs on Molecular Underpinnings, Prognosis, and Treatment Response in Pediatric Low-Grade Glioma
Kazerooni AF, Kraya A, Rathi KS, Kim MC, Vossough A, Khalili N, Familiar A, Gandhi D, Khalili N, Kesherwani V, Haldar D, Anderson H, Jin R, Mahtabfar A, Bagheri S, Guo Y, Li Q, Huang X, Zhu Y, [...] Nabavizadeh A
medRxiv, 19 Apr 2024
Cited by: 0 articles | PPR: PPR840859
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Comparison of Volumetric and 2D Measurements and Longitudinal Trajectories in the Response Assessment of BRAF V600E-Mutant Pediatric Gliomas in the Pacific Pediatric Neuro-Oncology Consortium Clinical Trial.
Ramakrishnan D, Brüningk SC, von Reppert M, Memon F, Maleki N, Aneja S, Kazerooni AF, Nabavizadeh A, Lin M, Bousabarah K, Molinaro A, Nicolaides T, Prados M, Mueller S, Aboian MS
AJNR Am J Neuroradiol, 45(4):475-482, 08 Apr 2024
Cited by: 0 articles | PMID: 38453411
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Reliability generalization meta-analysis of orthorexia nervosa using the ORTO-11/12/15/R scale in all populations and language versions.
Alshaibani L, Elmasry A, Kazerooni A, Alsaeed J, Alsendy K, Alaamer R, Buhassan Z, Alaqaili R, Ghazzawi H, Pandi-Perumal SR, Trabelsi K, Jahrami H
J Eat Disord, 12(1):39, 19 Mar 2024
Cited by: 1 article | PMID: 38504366 | PMCID: PMC10949742
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Early prognostication of overall survival for pediatric diffuse midline gliomas using MRI radiomics and machine learning: A two-center study.
Liu X, Jiang Z, Roth HR, Anwar SM, Bonner ER, Mahtabfar A, Packer RJ, Kazerooni AF, Bornhorst M, Linguraru MG
Neurooncol Adv, 6(1):vdae108, 01 Jan 2024
Cited by: 0 articles | PMID: 39027132 | PMCID: PMC11255990
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Subtyping Brain Diseases from Imaging Data
Wen J, Varol E, Yang Z, Hwang G, Dwyer D, Kazerooni AF, Lalousis PA, Davatzikos C
Humana, New York, NY, 20 Dec 2023
Cited by: 0 articles | PMID: 37988509
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Investigating the tendency to use COVID-19 vaccine booster dose in Iran.
Askarian M, Kazerooni AR, Shayan Z, Karimzadeh P, Movahedi M, Hatam N
BMC Health Serv Res, 23(1):1051, 02 Oct 2023
Cited by: 1 article | PMID: 37784095 | PMCID: PMC10544311
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Early prognostication of overall survival for pediatric diffuse midline gliomas using MRI radiomics and machine learning: a two-center study
Liu X, Jiang Z, Roth HR, Anwar SM, Bonner ER, Mahtabfar A, Packer RJ, Kazerooni AF, Bornhorst M, Linguraru MG
medRxiv, 02 Nov 2023
Cited by: 0 articles | PPR: PPR751956
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Physics-Informed Discretization for Reproducible and Robust Radiomic Feature Extraction Using Quantitative MRI.
Zhao W, Hu Z, Kazerooni AF, Körzdörfer G, Nittka M, Davatzikos C, Viswanath SE, Wang X, Badve C, Ma D
Invest Radiol, 59(5):359-371, 09 Oct 2023
Cited by: 0 articles | PMID: 37812483
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Systematic Literature Review of Machine Learning Algorithms Using Pretherapy Radiologic Imaging for Glioma Molecular Subtype Prediction.
Lost J, Verma T, Jekel L, von Reppert M, Tillmanns N, Merkaj S, Petersen GC, Bahar R, Gordem A, Haider MA, Subramanian H, Brim W, Ikuta I, Omuro A, Conte GM, Marquez-Nostra BV, Avesta A, Bousabarah K, Nabavizadeh A, [...] Aboian M
AJNR Am J Neuroradiol, 44(10):1126-1134, 01 Oct 2023
Cited by: 1 article | PMID: 37770204 | PMCID: PMC10549943
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Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas: results from the ReSPOND consortium.
Lee MD, Patel SH, Mohan S, Akbari H, Bakas S, Nasrallah MP, Calabrese E, Rudie J, Villanueva-Meyer J, LaMontagne P, Marcus DS, Colen RR, Balana C, Choi YS, Badve C, Barnholtz-Sloan JS, Sloan AE, Booth TC, Palmer JD, [...] ReSPOND Consortium
Neuroradiology, 65(9):1343-1352, 19 Jul 2023
Cited by: 8 articles | PMID: 37468750
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Radiomics for characterization of the glioma immune microenvironment.
Khalili N, Kazerooni AF, Familiar A, Haldar D, Kraya A, Foster J, Koptyra M, Storm PB, Resnick AC, Nabavizadeh A
NPJ Precis Oncol, 7(1):59, 19 Jun 2023
Cited by: 5 articles | PMID: 37337080 | PMCID: PMC10279670
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Toxicology and carcinogenesis studies of an isomeric mixture of tris(chloropropyl) phosphate administered in feed to Sprague Dawley (Hsd:Sprague Dawley SD) rats and B6C3F1/N mice.
National Toxicology Program
Natl Toxicol Program Tech Rep Ser, (602):NTP-TR-602, 01 Jun 2023
Cited by: 3 articles | PMID: 37368980
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The Radiogenomic and Spatiogenomic Landscapes of Glioblastoma, and their Relationship to Oncogenic Drivers
Kazerooni AF, Akbari H, Hu X, Bommineni V, Grigoriadis D, Toorens E, Sako C, Mamourian E, Ballinger D, Sussman R, Singh A, Verginadis II, Dahmane N, Koumenis C, Binder ZA, Bagley SJ, Mohan S, Hatzigeorgiou A, O’Rourke DM, [...] Davatzikos C
bioRxiv, 18 Dec 2022
Cited by: 0 articles | PPR: PPR586270
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Current state of pediatric neuro-oncology imaging, challenges and future directions.
Nabavizadeh A, Barkovich MJ, Mian A, Ngo V, Kazerooni AF, Villanueva-Meyer JE
Neoplasia, 37:100886, 10 Feb 2023
Cited by: 4 articles | PMID: 36774835 | PMCID: PMC9945752
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Automated Tumor Segmentation and Brain Tissue Extraction from Multiparametric MRI of Pediatric Brain Tumors: A Multi-Institutional Study
Kazerooni AF, Arif S, Madhogarhia R, Khalili N, Haldar D, Bagheri S, Familiar AM, Anderson H, Haldar S, Tu W, Kim MC, Viswanathan K, Muller S, Prados M, Kline C, Vidal L, Aboian M, Storm PB, Resnick AC, [...] Nabavizadeh A
medRxiv, 11 Jan 2023
Cited by: 0 articles | PPR: PPR595389
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Unsupervised machine learning using K-means identifies radiomic subgroups of pediatric low-grade gliomas that correlate with key molecular markers.
Haldar D, Kazerooni AF, Arif S, Familiar A, Madhogarhia R, Khalili N, Bagheri S, Anderson H, Shaikh IS, Mahtabfar A, Kim MC, Tu W, Ware J, Vossough A, Davatzikos C, Storm PB, Resnick A, Nabavizadeh A
Neoplasia, 36:100869, 23 Dec 2022
Cited by: 9 articles | PMID: 36566592 | PMCID: PMC9803939
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Estimating willingness to pay for diabetes complications.
Ghahramani S, Sepehrpoor M, Kazerooni AR, Jahromi AT, Khoshsoroor D, Barzegar D, Seifooripour R, Moradi N, Roodsarabi F, Manzouri A, Sayari M
Prim Care Diabetes, 16(6):829-836, 15 Oct 2022
Cited by: 0 articles | PMID: 36253327
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The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: advanced MRI, clinical, genomics, & radiomics.
Bakas S, Sako C, Akbari H, Bilello M, Sotiras A, Shukla G, Rudie JD, Santamaría NF, Kazerooni AF, Pati S, Rathore S, Mamourian E, Ha SM, Parker W, Doshi J, Baid U, Bergman M, Binder ZA, Verma R, [...] Davatzikos C
Sci Data, 9(1):453, 29 Jul 2022
Cited by: 27 articles | PMID: 35906241 | PMCID: PMC9338035
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Toxicity studies of select ionic liquids (1-ethyl-3-methylimidazolium chloride, 1-butyl-3-methylimidazolium chloride, 1-butyl-1-methylpyrrolidinium chloride, and n-butylpyridinium chloride) administered in drinking water to Sprague Dawley (Hsd:Sprague Dawley SD) rats and B6C3F1/N mice.
National Toxicology Program
Toxic Rep Ser, (103):NTP-TOX-103, 01 May 2022
Cited by: 2 articles | PMID: 35652689
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NIMG-73. CAPTURING GLIOBLASTOMA HETEROGENEITY USING IMAGING AND DEEP LEARNING: APPLICATION TO MGMT PROMOTER METHYLATION
Saxena S, Kazerooni A, Toorens E, Bakas S, Akbari H, Sako C, Mamourian E, Koumenis C, Mohan S, Bagley S, Lustig R, O’Rourke D, Ganguly T, Nasrallah M, Davatzikos C
Neuro Oncol, 23(suppl 6):vi146-vi146, 01 Nov 2021
Cited by: 0 articles | PMCID: PMC8598525
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NIMG-63. MACHINE LEARNING USING MRI RADIOMIC ANALYSIS TO PREDICT KI-67 IN WHO GRADE I MENINGIOMAS
Khanna O, Kazerooni A, Garcia J, Sako C, Arif S, Shi W, Davatzikos C
Neuro Oncol, 23(suppl 6):vi143-vi144, 01 Nov 2021
Cited by: 0 articles | PMCID: PMC8598698
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1-25 of 43 results

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Search life-sciences literature (45,100,050 articles, preprints and more)

Search results

Empowering Data Sharing in Neuroscience: A Deep Learning De-identification Method for Pediatric Brain MRIs.

Sex-Specific Differences in Patients with <i>IDH1</i>-Wild-Type Grade 4 Glioma in the ReSPOND Consortium.

A multi-institutional meningioma MRI dataset for automated multi-sequence image segmentation.

Active Learning in Brain Tumor Segmentation with Uncertainty Sampling and Annotation Redundancy Restriction.

Multiparametric MRI Along with Machine Learning Informs on Molecular Underpinnings, Prognosis, and Treatment Response in Pediatric Low-Grade Glioma

Comparison of Volumetric and 2D Measurements and Longitudinal Trajectories in the Response Assessment of BRAF V600E-Mutant Pediatric Gliomas in the Pacific Pediatric Neuro-Oncology Consortium Clinical Trial.

Reliability generalization meta-analysis of orthorexia nervosa using the ORTO-11/12/15/R scale in all populations and language versions.

Early prognostication of overall survival for pediatric diffuse midline gliomas using MRI radiomics and machine learning: A two-center study.

Subtyping Brain Diseases from Imaging Data

Investigating the tendency to use COVID-19 vaccine booster dose in Iran.

Early prognostication of overall survival for pediatric diffuse midline gliomas using MRI radiomics and machine learning: a two-center study

Physics-Informed Discretization for Reproducible and Robust Radiomic Feature Extraction Using Quantitative MRI.

Systematic Literature Review of Machine Learning Algorithms Using Pretherapy Radiologic Imaging for Glioma Molecular Subtype Prediction.

Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas: results from the ReSPOND consortium.

Radiomics for characterization of the glioma immune microenvironment.

Toxicology and carcinogenesis studies of an isomeric mixture of tris(chloropropyl) phosphate administered in feed to Sprague Dawley (Hsd:Sprague Dawley SD) rats and B6C3F1/N mice.

The Radiogenomic and Spatiogenomic Landscapes of Glioblastoma, and their Relationship to Oncogenic Drivers

Current state of pediatric neuro-oncology imaging, challenges and future directions.

Automated Tumor Segmentation and Brain Tissue Extraction from Multiparametric MRI of Pediatric Brain Tumors: A Multi-Institutional Study

Unsupervised machine learning using K-means identifies radiomic subgroups of pediatric low-grade gliomas that correlate with key molecular markers.

Estimating willingness to pay for diabetes complications.

The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: advanced MRI, clinical, genomics, & radiomics.

Toxicity studies of select ionic liquids (1-ethyl-3-methylimidazolium chloride, 1-butyl-3-methylimidazolium chloride, 1-butyl-1-methylpyrrolidinium chloride, and n-butylpyridinium chloride) administered in drinking water to Sprague Dawley (Hsd:Sprague Dawley SD) rats and B6C3F1/N mice.

NIMG-73. CAPTURING GLIOBLASTOMA HETEROGENEITY USING IMAGING AND DEEP LEARNING: APPLICATION TO MGMT PROMOTER METHYLATION

NIMG-63. MACHINE LEARNING USING MRI RADIOMIC ANALYSIS TO PREDICT KI-67 IN WHO GRADE I MENINGIOMAS

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