An In Silico Approach toward the Appropriate Absorption Rate Metric in Bioequivalence von Karalis, Vangelis D

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Machine Learning in Bioequivalence: Towards Identifying an Appropriate Measure of Absorption Rate von Karalis, Vangelis D.

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On the Interplay between Machine Learning, Population Pharmacokinetics, and Bioequivalence to Introduce Average Slope as a New Measure for Absorption Rate von Karalis, Vangelis D.

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A Vector Theory of Assessing Clinical Trials: An Application to Bioequivalence von Karalis, Vangelis D

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Development and validation of a prognostic and predictive 32-gene signature for gastric cancer von Cheong, Jae-Ho, Wang, Sam C., Park, Sunho, Porembka, Matthew R., Christie, Alana L., Kim, Hyunki, Kim, Hyo Song, Zhu, Hong, Hyung, Woo Jin, Noh, Sung Hoon, Hu, Bo, Hong, Changjin, Karalis, John D., Kim, In-Ho, Lee, Sung Hak, Hwang, Tae Hyun

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Variational Autoencoders for Data Augmentation in Clinical Studies von Papadopoulos, Dimitris, Karalis, Vangelis D

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Introducing an Artificial Neural Network for Virtually Increasing the Sample Size of Bioequivalence Studies von Papadopoulos, Dimitris, Karalis, Vangelis D

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Average Slope vs. Cmax: Which Truly Reflects the Drug-Absorption Rate? von Kokkali, Maria, Karalis, Vangelis D

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Implementation of a Generative AI Algorithm for Virtually Increasing the Sample Size of Clinical Studies von Nikolopoulos, Anastasios, Karalis, Vangelis D

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Bioequivalence Studies of Highly Variable Drugs: An Old Problem Addressed by Artificial Neural Networks von Papadopoulos, Dimitris, Karali, Georgia, Karalis, Vangelis D.

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The Integration of Artificial Intelligence into Clinical Practice von Karalis, Vangelis D.

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ASO Visual Abstract: Hospital Designations and Their Impact on Guideline-Concordant Care and Survival in Pancreatic Cancer: Do They Matter? von Murimwa, Gilbert Z., Karalis, John D., Meier, Jennie, Yan, Jingsheng, Zhu, Hong, Hester, Caitlin A., Porembka, Matthew R., Wang, Sam C., Mansour, John C., Zeh, Herbert J., Yopp, Adam C., Polanco, Patricio M.

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Correction to: Lenvatinib inhibits the growth of gastric cancer patient‑derived xenografts generated from a heterogeneous populations von Karalis, John D, Yoon, Lynn Y, Hammer, Suntrea T G, Hong, Changjin, Zhu, Min, Nassour, Ibrahim, Ju, Michelle R, Xiao, Shu, Castro-Dubon, Esther C, Agrawal, Deepak, Suarez, Jorge, Reznik, Scott I, Mansour, John C, Polanco, Patricio M, Yopp, Adam C, Zeh Iii, Herbert J, Hwang, Tae Hyun, Zhu, Hao, Porembka, Matthew R, Wang, Sam C

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Lenvatinib inhibits the growth of gastric cancer patient-derived xenografts generated from a heterogeneous population von Karalis, John D, Yoon, Lynn Y, Hammer, Suntrea T G, Hong, Changjin, Zhu, Min, Nassour, Ibrahim, Ju, Michelle R, Xiao, Shu, Castro-Dubon, Esther C, Agrawal, Deepak, Suarez, Jorge, Reznik, Scott I, Mansour, John C, Polanco, Patricio M, Yopp, Adam C, Zeh, 3rd, Herbert J, Hwang, Tae Hyun, Zhu, Hao, Porembka, Matthew R, Wang, Sam C

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Alirocumab safety in people with and without diabetes mellitus: pooled data from 14 ODYSSEY trials von Leiter, L. A., Tinahones, F. J., Karalis, D. G., Bujas‐Bobanovic, M., Letierce, A., Mandel, J., Samuel, R., Jones, P. H.

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Incidental Solitary Adrenal Metastasis as the Initial Manifestation of a Solid Variant of Papillary Thyroid Carcinoma, With Emphasis on Pathologic Diagnosis and Clinical Management von Karalis, John D., Jia, Liwei, Murvelashvili, Natia, Vora, Amy, Tessnow, Alex, Dackiw, Alan P.B.

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ASO Author Reflections: Novel Methodology to Define High-Volume Centers for Complex Cancer Operations von Karalis, John D., Ju, Michelle R., Porembka, Matthew R.

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Machine Learning in Allergic Contact Dermatitis: Identifying (Dis)similarities between Polysensitized and Monosensitized Patients von Kyritsi, Aikaterini, Tagka, Anna, Stratigos, Alexander, Karalis, Vangelis D.

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The Colorectal Cancer Tumor Microenvironment and Its Impact on Liver and Lung Metastasis von Chandra, Raghav, Karalis, John D, Liu, Charles, Murimwa, Gilbert Z, Voth Park, Josiah, Heid, Christopher A, Reznik, Scott I, Huang, Emina, Minna, John D, Brekken, Rolf A

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ASO Author Reflections: Identification of High-Performing Veterans Affairs Health System Regions to Improve Patient Outcomes of Veterans with Hepatocellular Carcinoma von Karalis, John D., Ju, Michelle R., Polanco, Patricio M.

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