Citations 2
Predicting therapeutic clinical trial enrollment for adult patients with low- and high-grade glioma using supervised machine learning
Mehari, Mulki , Warrier, Gayathri , Dada, Abraham , Kabir, Aymen , Haskell-Mendoza, Aden , Tripathy, Arushi , Jha, Rohan , Nieblas‐Bedolla, Edwin , Jackson, Joshua , Gonzalez, Ariel T , Reason, Ellery , Flusché, Ann Marie , Reihl, Sheantel , Dalton, Tara , Negussie, Mikias , Gonzales, Cesar Nava, Ambati, Vardhaan , Desjardins, Annick , Krishna, Saritha, Chang, Susan M. , Porter, Alyx B. , Fecci, Peter E. , Hollon, Todd , Chukwueke, Ugonma , Badal, Kimberly , Molinaro, Annette M. , Hervey‐Jumper, Shawn L. , Haskell-Mendoza, Aden P , Reason, Ellery H , Ambati, Vardhaan , Krishna, Saritha , Porter, Alyx , Hollon, Todd , Chukwueke, Ugonma N , Badal, Kimberly , Molinaro, Annette M. , Hervey-Jumper, Shawn L , Reihl, Sheantel J , Fecci, Peter E , Desjardins, Annick , Daniel, Andy G. S.
Science Advances | June 11, 2025 | Volume: 11 | Issue: 23 | Pages: No page available
Therapeutic clinical trial enrollment does not match glioma incidence across demographics. Traditional statistical methods have identified independent predictors of trial enrollment; however, our understanding of the interactions between these factors remains limited. To test the interactive effects of demographic, socioeconomic, and oncologic variables on trial enrollment, we designed boosted neural networks (BNNs) for all glioma patients ( n = 1042), women ( n = 445, 42.7%), and minorities ( n = 151, 14.5%) and externally validated these models [whole cohort, n = 230; women, n = 89 (38.7%); minority, n = 66 (28.7%)]. For the whole-cohort BNN, the most influential variables on enrollment were oncologic variables, including KPS [total effect (TE), 0.327], chemotherapy (TE, 0.326), tumor location (TE, 0.322), and seizures (TE, 0.239). The women-only BNN exhibited a similar trend. Conversely, for the minority-only BNN, socioeconomic variables [insurance status (TE, 0.213), occupation classification (TE, 0.204), and employment status (TE, 0.150)] were most influential. These results may help prioritize patient-specific initiatives to increase accrual.
Tonic Serotonin Measurements In Vivo Using N-Shaped Multiple Cyclic Square Wave Voltammetry
Shin, Hojin , Goyal, Abhinav , Barnett, J. Hudson , Rusheen, Aaron E. , Jha, Rohan , Hwang, Sang Mun, Kang, Yumin , Park, Cheonho , Cho, Hyun‐U , Bennet, Kevin E. , Heien, Michael L. , Jang, Dong Pyo , Lee, Kendall H. , Yuen, Jason , Kang, Yumin , Oh, Yoonbae , Heien, Michael L , Jang, Dong Pyo , Jha, Rohan, Blaha, Charles D. , Oh, Yoonbae
Analytical Chemistry | December 2, 2021 | Volume: 93 | Issue: 51 | Pages: 16987-16994