Panagiotis Korfiatis

20 papers Journal 18Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Large language models in real-world clinical workflows: a systematic review of applications and implementation. Frontiers Digit. Health Yaara Artsi, Vera Sorin, Benjamin S. Glicksberg, Panagiotis Korfiatis, Girish N. Nadkarni, Eyal Klang
2025	J	`jnl`	Reasoning red teaming in healthcare not all paths to a desired outcome are desirable. npj Digit. Medicine Vera Sorin, Panagiotis Korfiatis, Girish N. Nadkarni, Eyal Klang
2025	J	`jnl`	Socio-Demographic Modifiers Shape Large Language Models' Ethical Decisions. J. Heal. Informatics Res. Vera Sorin, Panagiotis Korfiatis, Jeremy D. Collins, Donald Apakama, Mahmud Omar, Benjamin S. Glicksberg, Mei-Ean Yeow, Megan Brandeland, Girish N. Nadkarni, Eyal Klang
2024	J	`jnl`	A Classification-Based Adaptive Segmentation Pipeline: Feasibility Study Using Polycystic Liver Disease and Metastases from Colorectal Cancer CT Images. CoRR Peilong Wang, Timothy L. Kline, Andy D. Missert, Cole J. Cook, Matthew R. Callstrom, Alex Chan, Robert P. Hartman, Zachary S. Kelm, Panagiotis Korfiatis
2024	J	`jnl`	A Classification-Based Adaptive Segmentation Pipeline: Feasibility Study Using Polycystic Liver Disease and Metastases from Colorectal Cancer CT Images. J. Imaging Inform. Medicine Peilong Wang, Timothy L. Kline, Andy D. Missert, Cole J. Cook, Matthew R. Callstrom, Alex Chan, Robert P. Hartman, Zachary S. Kelm, Panagiotis Korfiatis
2023	—	`conf`	A Texture Neural Network to Predict the Abnormal Brachial Plexus from Routine Magnetic Resonance Imaging. MICCAI (8) Weiguo Cao, Benjamin Howe, Nicholas Rhodes, Sumana Ramanathan, Panagiotis Korfiatis, Kimberly Amrami, Robert Spinner, Timothy Kline
2023	J	`jnl`	AI in the Loop - Functionalizing Fold Performance Disagreement to Monitor Automated Medical Image Segmentation Pipelines. CoRR Harrison C. Gottlich, Panagiotis Korfiatis, Adriana V. Gregory, Timothy L. Kline
2023	J	`jnl`	Effect of Dataset Size and Medical Image Modality on Convolutional Neural Network Model Performance for Automated Segmentation: A CT and MR Renal Tumor Imaging Study. J. Digit. Imaging Harrison C. Gottlich, Adriana V. Gregory, Vidit Sharma, Abhinav Khanna, Amr U. Moustafa, Christine M. Lohse, Theodora A. Potretzke, Panagiotis Korfiatis, Aaron M. Potretzke, Aleksandar Denic, Andrew D. Rule, Naoki Takahashi, Bradley J. Erickson, Bradley C. Leibovich, Timothy L. Kline
2023	J	`jnl`	Role of Image Acquisition and Patient Phenotype Variations in Automatic Segmentation Model Generalization. CoRR Timothy L. Kline, Sumana Ramanathan, Harrison C. Gottlich, Panagiotis Korfiatis, Adriana V. Gregory
2022	J	`jnl`	Reproducibility in medical image radiomic studies: contribution of dynamic histogram binning. CoRR Darryl E. Wright, Cole J. Cook, Jason Klug, Panagiotis Korfiatis, Timothy L. Kline
2021	J	`jnl`	AI Integration in the Clinical Workflow. J. Digit. Imaging Daniel J. Blezek, Lonny Olson-Williams, Andrew Missert, Panagiotis Korfiatis
2021	J	`jnl`	Deep Learning Improves the Temporal Reproducibility of Aortic Measurement. J. Digit. Imaging Alex Bratt, Daniel J. Blezek, William J. Ryan, Kenneth A. Philbrick, Prabhakar Rajiah, Yasmeen K. Tandon, Lara A. Walkoff, Jason C. Cai, Emily N. Sheedy, Panagiotis Korfiatis, Eric E. Williamson, Bradley J. Erickson, Jeremy D. Collins
2019	J	`jnl`	High Resolution Medical Image Analysis with Spatial Partitioning. CoRR Le Hou, Youlong Cheng, Noam Shazeer, Niki Parmar, Yeqing Li, Panagiotis Korfiatis, Travis M. Drucker, Daniel J. Blezek, Xiaodan Song
2019	J	`jnl`	Interactive segmentation of medical images through fully convolutional neural networks. CoRR Tomas Sakinis, Fausto Milletari, Holger Roth, Panagiotis Korfiatis, Petro M. Kostandy, Kenneth Philbrick, Zeynettin Akkus, Ziyue Xu, Daguang Xu, Bradley J. Erickson
2019	J	`jnl`	RIL-Contour: a Medical Imaging Dataset Annotation Tool for and with Deep Learning. J. Digit. Imaging Kenneth A. Philbrick, Alexander D. Weston, Zeynettin Akkus, Timothy L. Kline, Panagiotis Korfiatis, Tomas Sakinis, Petro M. Kostandy, Arunnit Boonrod, Atefeh Zeinoddini, Naoki Takahashi, Bradley J. Erickson
2018	J	`jnl`	Differences Between Schizophrenic and Normal Subjects Using Network Properties from fMRI. J. Digit. Imaging Youngoh Bae, Kunaraj Kumarasamy, Issa Ali, Panagiotis Korfiatis, Zeynettin Akkus, Bradley J. Erickson
2018	—	`conf`	Evaluation of a deep learning architecture for MR imaging prediction of ATRX in glioma patients. Computer-Aided Diagnosis Panagiotis Korfiatis, Timothy L. Kline, Bradley J. Erickson
2017	J	`jnl`	Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys. J. Digit. Imaging Timothy L. Kline, Panagiotis Korfiatis, Marie E. Edwards, Jaime D. Blais, Frank S. Czerwiec, Peter C. Harris, Bernard F. King, Vicente E. Torres, Bradley J. Erickson
2017	J	`jnl`	Residual Deep Convolutional Neural Network Predicts MGMT Methylation Status. J. Digit. Imaging Panagiotis Korfiatis, Timothy L. Kline, Daniel H. Lachance, Ian F. Parney, Jan C. Buckner, Bradley J. Erickson
2017	J	`jnl`	Toolkits and Libraries for Deep Learning. J. Digit. Imaging Bradley J. Erickson, Panagiotis Korfiatis, Zeynettin Akkus, Timothy Kline, Kenneth Philbrick