Yixi Xu

Sr. Applied Research Scientist

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Publications

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- Towards reliable use of artificial intelligence to classify otitis media using otoscopic images: Addressing bias and improving data quality
  
  Yixi Xu, Al-Rahim Habib, Graeme Crossland, Hemi Patel, Chris Perry, Kris Bock, Tony Lian, Bill Weeks, Rahul Dodhia, Juan M. Lavista Ferres, Narinder Pal Singh
  
  PLOS One | May 2026
  
  Publication PDF DOI Project
- AI Research as a Continuous Clinical Service
  
  Yixi Xu, Rahul Dodhia, Juan M. Lavista Ferres, Bill Weeks
  
  Mayo Clinic Proceedings: Digital Health | December 2025
  
  Publication DOI PDF Project
- Liver MRI proton density fat fraction inference from contrast enhanced CT images using deep learning: A proof-of-concept study
  
  Md Nasir, Yixi Xu, Kyle Hasenstab, Alekhya Yechoor, Rahul Dodhia, Bill Weeks, Juan M. Lavista Ferres, Guilherme Moura Cunha
  
  PloS One | August 2025
  
  Publication PDF Project
- Cancer Detection in Breast MRI Screening via Explainable AI Anomaly Detection
  
  Felipe Oviedo, Anum S. Kazerouni, Philipp Liznerski, Yixi Xu, Michael Hirano, Robert A. Vandermeulen, Marius Kloft, Elyse Blum, Adam M. Alessio, Christopher I. Li, Bill Weeks, Rahul Dodhia, Juan M. Lavista Ferres, Habib Rahbar, Savannah C. Partridge
  
  Radiology | July 2025
  
  Publication PDF Project
- Rapid and accurate prediction of protein homo-oligomer symmetry using Seq2Symm
  
  Meghana Kshirsagar, Artur Meller, Ian R. Humphreys, Samuel Sledzieski, Yixi Xu, Rahul Dodhia, Eric Horvitz, Bonnie Berger, Gregory R. Bowman, Juan M. Lavista Ferres, David Baker, Minkyung Baek
  
  Nature Communications | February 2025
  
  Publication PDF Project
- Towards an automated Segment Anything Model (SAM) for lesion segmentation in oncological PET/CT images
  
  S. Ahamed, Yixi Xu, Rahul Dodhia, Bill Weeks, Juan M. Lavista Ferres, A. Rahmim
  
  2023 IEEE Nuclear Science Symposium | December 2023
  
  Publication DOI Project
- Comprehensive Evaluation and Insights into the Use of Deep Neural Networks to Detect and Quantify Lymphoma Lesions in PET/CT Images
  
  Shadab Ahamed, Yixi Xu, C. Gowdy, O. JooH., I. Bloise, Don Wilson, Patrick Martineau, François Bénard, F. Yousefirizi, Rahul Dodhia, Juan M. Lavista Ferres, Bill Weeks, Carlos F. Uribe, Arman Rahmim
  
  November 2023
  
  DOI Publication Github
- Evaluating the Generalizability of Deep Learning Image Classification Algorithms to Detect Middle Ear Disease Using Otoscopy
  
  Al-Rahim Habib, Yixi Xu, Kris Bock, Shrestha Mohanty, Tina Sederholm, Bill Weeks, Rahul Dodhia, Juan M. Lavista Ferres, Chris Perry, Raymond Sacks, Narinder Singh
  
  Scientific Reports | April 2023
  
  Publication Project
- Automatic segmentation of prostate cancer metastases in PSMA PET/CT images using deep neural networks with weighted batch-wise dice loss
  
  Yixi Xu, Ivan Klyuzhin, Sara Harsini, Anthony Ortiz, Shun Zhang, François Bénard, Rahul Dodhia, Carlos F. Uribe, Arman Rahmim , Juan M. Lavista Ferres
  
  Computers in Biology and Medicine | April 2023
  
  Publication DOI Project Project
- A slice classification neural network for automated classification of axial PET/CT slices from a multi-centric lymphoma dataset
  
  Shadab Ahamed, Yixi Xu, Ingrid Bloise, Joo H. O., Carlos F. Uribe, Rahul Dodhia, Juan M. Lavista Ferres, Arman Rahmim
  
  Medical Imaging 2023 | April 2023
  
  Publication Project
- Identifying long-term effects of SARS-CoV-2 and their association with social determinants of health in a cohort of over one million COVID-19 survivors
  
  Sumit Mukherjee, Meghana Kshirsagar, Nicholas Becker, Yixi Xu, Bill Weeks, Shwetak Patel, Juan M. Lavista Ferres, Michael L. Jackson
  
  BMC Public Health | December 2022
  
  Publication PDF Project Project
- MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models
  
  Yixi Xu, Sumit Mukherjee, Xiyang Liu, Shruti Tople, Rahul Dodhia, Juan M. Lavista Ferres
  
  Transactions on Machine Learning Research (TMLR) | October 2022
  
  Publication Project Project
- Machine Learning-based Derivation and External Validation of a Tool to Predict Death and Development of Organ Failure in Hospitalized Patients with COVID-19
  
  Yixi Xu, Anusua Trivedi, Nicholas Becker, Marian Blazes, Juan M. Lavista Ferres, Dr. Aaron Lee, W Liles, Dr. Pavan Bhatraju
  
  Scientific Reports | October 2022
  
  Publication PDF Project Project
- Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features
  
  Ivan S. Klyuzhin, Juan M. Lavista Ferres, Yixi Xu, Anthony Ortiz, Ghassan Hamarneh, Arman Rahmim
  
  ScienceDirect | June 2022
  
  Publication Project
- Reimagining Leprosy Elimination with AI Analysis of a Combination of Skin Lesion Images with Demographic and Clinical Data
  
  Raquel R Barbieri, Yixi Xu, Lucy Setian, Paulo Thiago Souza-Santos, Anusua Trivedi, Jim Cristofono, Ricardo Bhering, Kevin White, Anna M Sales, Geralyn Miller, José Augusto C Nery, Michael Sharman, Richard Bumann, Shun Zhang, Mohamad Goldust, Euzenir N Sarno, Fareed Mirza, Arielle Cavaliero, Sander Timmer, Elena Bonfiglioli, Cairns Smith, David Scollard, Alexander A Navarini, Ann Aerts, Juan M. Lavista Ferres, Milton O Moraes
  
  Science Direct | January 2022
  
  Publication PDF Project Project
- Unsupervised Background Removal by Dual-Modality PET/CT Guidance: Application to PSMA Imaging of Metastases
  
  Ivan Klyuzhin, Yixi Xu, Sara Harsini, Anthony Ortiz, Carlos Uribe, Juan M. Lavista Ferres, Arman Rahmim
  
  Journal of Nuclear Medicine | May 2021
  
  Publication Project
- Becoming Good at AI for Good
  
  Meghana Kshirsagar, Siyu Yang, Caleb Robinson, Shahrzad Gholami, Ivan Klyuzhin, Sumit Mukherjee, Md Nasir, Anthony Ortiz, Felipe Oviedo, Darren Tanner, Anusua Trivedi, Yixi Xu, Ming Zhong, Bistra Dilkina, Rahul Dodhia, Juan M. Lavista Ferres
  
  AAAI/ACM Conference on AI, Ethics, and Society (AIES'21) | April 2021
  
  Publication
- privGAN: Protecting GANs from membership inference attacks at low cost
  
  Sumit Mukherjee, Yixi Xu, Anusua Trivedi, Juan M. Lavista Ferres
  
  May 2020
  
  Under major revision at PETS
  
  Publication

- Towards reliable use of artificial intelligence to classify otitis media using otoscopic images: Addressing bias and improving data quality
  
  Yixi Xu, Al-Rahim Habib, Graeme Crossland, Hemi Patel, Chris Perry, Kris Bock, Tony Lian, Bill Weeks, Rahul Dodhia, Juan M. Lavista Ferres, Narinder Pal Singh
  
  PLOS One | May 2026
  
  Publication PDF DOI Project
- AI Research as a Continuous Clinical Service
  
  Yixi Xu, Rahul Dodhia, Juan M. Lavista Ferres, Bill Weeks
  
  Mayo Clinic Proceedings: Digital Health | December 2025
  
  Publication DOI PDF Project
- Liver MRI proton density fat fraction inference from contrast enhanced CT images using deep learning: A proof-of-concept study
  
  Md Nasir, Yixi Xu, Kyle Hasenstab, Alekhya Yechoor, Rahul Dodhia, Bill Weeks, Juan M. Lavista Ferres, Guilherme Moura Cunha
  
  PloS One | August 2025
  
  Publication PDF Project
- Cancer Detection in Breast MRI Screening via Explainable AI Anomaly Detection
  
  Felipe Oviedo, Anum S. Kazerouni, Philipp Liznerski, Yixi Xu, Michael Hirano, Robert A. Vandermeulen, Marius Kloft, Elyse Blum, Adam M. Alessio, Christopher I. Li, Bill Weeks, Rahul Dodhia, Juan M. Lavista Ferres, Habib Rahbar, Savannah C. Partridge
  
  Radiology | July 2025
  
  Publication PDF Project
- Rapid and accurate prediction of protein homo-oligomer symmetry using Seq2Symm
  
  Meghana Kshirsagar, Artur Meller, Ian R. Humphreys, Samuel Sledzieski, Yixi Xu, Rahul Dodhia, Eric Horvitz, Bonnie Berger, Gregory R. Bowman, Juan M. Lavista Ferres, David Baker, Minkyung Baek
  
  Nature Communications | February 2025
  
  Publication PDF Project
- Towards an automated Segment Anything Model (SAM) for lesion segmentation in oncological PET/CT images
  
  S. Ahamed, Yixi Xu, Rahul Dodhia, Bill Weeks, Juan M. Lavista Ferres, A. Rahmim
  
  2023 IEEE Nuclear Science Symposium | December 2023
  
  Publication DOI Project
- Comprehensive Evaluation and Insights into the Use of Deep Neural Networks to Detect and Quantify Lymphoma Lesions in PET/CT Images
  
  Shadab Ahamed, Yixi Xu, C. Gowdy, O. JooH., I. Bloise, Don Wilson, Patrick Martineau, François Bénard, F. Yousefirizi, Rahul Dodhia, Juan M. Lavista Ferres, Bill Weeks, Carlos F. Uribe, Arman Rahmim
  
  November 2023
  
  DOI Publication Github
- Evaluating the Generalizability of Deep Learning Image Classification Algorithms to Detect Middle Ear Disease Using Otoscopy
  
  Al-Rahim Habib, Yixi Xu, Kris Bock, Shrestha Mohanty, Tina Sederholm, Bill Weeks, Rahul Dodhia, Juan M. Lavista Ferres, Chris Perry, Raymond Sacks, Narinder Singh
  
  Scientific Reports | April 2023
  
  Publication Project
- Automatic segmentation of prostate cancer metastases in PSMA PET/CT images using deep neural networks with weighted batch-wise dice loss
  
  Yixi Xu, Ivan Klyuzhin, Sara Harsini, Anthony Ortiz, Shun Zhang, François Bénard, Rahul Dodhia, Carlos F. Uribe, Arman Rahmim , Juan M. Lavista Ferres
  
  Computers in Biology and Medicine | April 2023
  
  Publication DOI Project Project
- A slice classification neural network for automated classification of axial PET/CT slices from a multi-centric lymphoma dataset
  
  Shadab Ahamed, Yixi Xu, Ingrid Bloise, Joo H. O., Carlos F. Uribe, Rahul Dodhia, Juan M. Lavista Ferres, Arman Rahmim
  
  Medical Imaging 2023 | April 2023
  
  Publication Project
- MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models
  
  Yixi Xu, Sumit Mukherjee, Xiyang Liu, Shruti Tople, Rahul Dodhia, Juan M. Lavista Ferres
  
  Transactions on Machine Learning Research (TMLR) | October 2022
  
  Publication Project Project
- Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features
  
  Ivan S. Klyuzhin, Juan M. Lavista Ferres, Yixi Xu, Anthony Ortiz, Ghassan Hamarneh, Arman Rahmim
  
  ScienceDirect | June 2022
  
  Publication Project
- Unsupervised Background Removal by Dual-Modality PET/CT Guidance: Application to PSMA Imaging of Metastases
  
  Ivan Klyuzhin, Yixi Xu, Sara Harsini, Anthony Ortiz, Carlos Uribe, Juan M. Lavista Ferres, Arman Rahmim
  
  Journal of Nuclear Medicine | May 2021
  
  Publication Project
- Becoming Good at AI for Good
  
  Meghana Kshirsagar, Siyu Yang, Caleb Robinson, Shahrzad Gholami, Ivan Klyuzhin, Sumit Mukherjee, Md Nasir, Anthony Ortiz, Felipe Oviedo, Darren Tanner, Anusua Trivedi, Yixi Xu, Ming Zhong, Bistra Dilkina, Rahul Dodhia, Juan M. Lavista Ferres
  
  AAAI/ACM Conference on AI, Ethics, and Society (AIES'21) | April 2021
  
  Publication
- privGAN: Protecting GANs from membership inference attacks at low cost
  
  Sumit Mukherjee, Yixi Xu, Anusua Trivedi, Juan M. Lavista Ferres
  
  May 2020
  
  Under major revision at PETS
  
  Publication
- Towards reliable use of artificial intelligence to classify otitis media using otoscopic images: Addressing bias and improving data quality
  
  Yixi Xu, Al-Rahim Habib, Graeme Crossland, Hemi Patel, Chris Perry, Kris Bock, Tony Lian, Bill Weeks, Rahul Dodhia, Juan M. Lavista Ferres, Narinder Pal Singh
  
  PLOS One | May 2026
  
  Publication PDF DOI Project
- Liver MRI proton density fat fraction inference from contrast enhanced CT images using deep learning: A proof-of-concept study
  
  Md Nasir, Yixi Xu, Kyle Hasenstab, Alekhya Yechoor, Rahul Dodhia, Bill Weeks, Juan M. Lavista Ferres, Guilherme Moura Cunha
  
  PloS One | August 2025
  
  Publication PDF Project
- Cancer Detection in Breast MRI Screening via Explainable AI Anomaly Detection
  
  Felipe Oviedo, Anum S. Kazerouni, Philipp Liznerski, Yixi Xu, Michael Hirano, Robert A. Vandermeulen, Marius Kloft, Elyse Blum, Adam M. Alessio, Christopher I. Li, Bill Weeks, Rahul Dodhia, Juan M. Lavista Ferres, Habib Rahbar, Savannah C. Partridge
  
  Radiology | July 2025
  
  Publication PDF Project
- Rapid and accurate prediction of protein homo-oligomer symmetry using Seq2Symm
  
  Meghana Kshirsagar, Artur Meller, Ian R. Humphreys, Samuel Sledzieski, Yixi Xu, Rahul Dodhia, Eric Horvitz, Bonnie Berger, Gregory R. Bowman, Juan M. Lavista Ferres, David Baker, Minkyung Baek
  
  Nature Communications | February 2025
  
  Publication PDF Project
- Towards an automated Segment Anything Model (SAM) for lesion segmentation in oncological PET/CT images
  
  S. Ahamed, Yixi Xu, Rahul Dodhia, Bill Weeks, Juan M. Lavista Ferres, A. Rahmim
  
  2023 IEEE Nuclear Science Symposium | December 2023
  
  Publication DOI Project
- Comprehensive Evaluation and Insights into the Use of Deep Neural Networks to Detect and Quantify Lymphoma Lesions in PET/CT Images
  
  Shadab Ahamed, Yixi Xu, C. Gowdy, O. JooH., I. Bloise, Don Wilson, Patrick Martineau, François Bénard, F. Yousefirizi, Rahul Dodhia, Juan M. Lavista Ferres, Bill Weeks, Carlos F. Uribe, Arman Rahmim
  
  November 2023
  
  DOI Publication Github
- Evaluating the Generalizability of Deep Learning Image Classification Algorithms to Detect Middle Ear Disease Using Otoscopy
  
  Al-Rahim Habib, Yixi Xu, Kris Bock, Shrestha Mohanty, Tina Sederholm, Bill Weeks, Rahul Dodhia, Juan M. Lavista Ferres, Chris Perry, Raymond Sacks, Narinder Singh
  
  Scientific Reports | April 2023
  
  Publication Project
- Automatic segmentation of prostate cancer metastases in PSMA PET/CT images using deep neural networks with weighted batch-wise dice loss
  
  Yixi Xu, Ivan Klyuzhin, Sara Harsini, Anthony Ortiz, Shun Zhang, François Bénard, Rahul Dodhia, Carlos F. Uribe, Arman Rahmim , Juan M. Lavista Ferres
  
  Computers in Biology and Medicine | April 2023
  
  Publication DOI Project Project
- A slice classification neural network for automated classification of axial PET/CT slices from a multi-centric lymphoma dataset
  
  Shadab Ahamed, Yixi Xu, Ingrid Bloise, Joo H. O., Carlos F. Uribe, Rahul Dodhia, Juan M. Lavista Ferres, Arman Rahmim
  
  Medical Imaging 2023 | April 2023
  
  Publication Project
- Identifying long-term effects of SARS-CoV-2 and their association with social determinants of health in a cohort of over one million COVID-19 survivors
  
  Sumit Mukherjee, Meghana Kshirsagar, Nicholas Becker, Yixi Xu, Bill Weeks, Shwetak Patel, Juan M. Lavista Ferres, Michael L. Jackson
  
  BMC Public Health | December 2022
  
  Publication PDF Project Project
- Machine Learning-based Derivation and External Validation of a Tool to Predict Death and Development of Organ Failure in Hospitalized Patients with COVID-19
  
  Yixi Xu, Anusua Trivedi, Nicholas Becker, Marian Blazes, Juan M. Lavista Ferres, Dr. Aaron Lee, W Liles, Dr. Pavan Bhatraju
  
  Scientific Reports | October 2022
  
  Publication PDF Project Project
- Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features
  
  Ivan S. Klyuzhin, Juan M. Lavista Ferres, Yixi Xu, Anthony Ortiz, Ghassan Hamarneh, Arman Rahmim
  
  ScienceDirect | June 2022
  
  Publication Project
- Reimagining Leprosy Elimination with AI Analysis of a Combination of Skin Lesion Images with Demographic and Clinical Data
  
  Raquel R Barbieri, Yixi Xu, Lucy Setian, Paulo Thiago Souza-Santos, Anusua Trivedi, Jim Cristofono, Ricardo Bhering, Kevin White, Anna M Sales, Geralyn Miller, José Augusto C Nery, Michael Sharman, Richard Bumann, Shun Zhang, Mohamad Goldust, Euzenir N Sarno, Fareed Mirza, Arielle Cavaliero, Sander Timmer, Elena Bonfiglioli, Cairns Smith, David Scollard, Alexander A Navarini, Ann Aerts, Juan M. Lavista Ferres, Milton O Moraes
  
  Science Direct | January 2022
  
  Publication PDF Project Project
- Unsupervised Background Removal by Dual-Modality PET/CT Guidance: Application to PSMA Imaging of Metastases
  
  Ivan Klyuzhin, Yixi Xu, Sara Harsini, Anthony Ortiz, Carlos Uribe, Juan M. Lavista Ferres, Arman Rahmim
  
  Journal of Nuclear Medicine | May 2021
  
  Publication Project
- Comprehensive Evaluation and Insights into the Use of Deep Neural Networks to Detect and Quantify Lymphoma Lesions in PET/CT Images
  
  Shadab Ahamed, Yixi Xu, C. Gowdy, O. JooH., I. Bloise, Don Wilson, Patrick Martineau, François Bénard, F. Yousefirizi, Rahul Dodhia, Juan M. Lavista Ferres, Bill Weeks, Carlos F. Uribe, Arman Rahmim
  
  November 2023
  
  DOI Publication Github
- privGAN: Protecting GANs from membership inference attacks at low cost
  
  Sumit Mukherjee, Yixi Xu, Anusua Trivedi, Juan M. Lavista Ferres
  
  May 2020
  
  Under major revision at PETS
  
  Publication
- MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models
  
  Yixi Xu, Sumit Mukherjee, Xiyang Liu, Shruti Tople, Rahul Dodhia, Juan M. Lavista Ferres
  
  Transactions on Machine Learning Research (TMLR) | October 2022
  
  Publication Project Project
- privGAN: Protecting GANs from membership inference attacks at low cost
  
  Sumit Mukherjee, Yixi Xu, Anusua Trivedi, Juan M. Lavista Ferres
  
  May 2020
  
  Under major revision at PETS
  
  Publication

- Towards reliable use of artificial intelligence to classify otitis media using otoscopic images: Addressing bias and improving data quality
  
  Yixi Xu, Al-Rahim Habib, Graeme Crossland, Hemi Patel, Chris Perry, Kris Bock, Tony Lian, Bill Weeks, Rahul Dodhia, Juan M. Lavista Ferres, Narinder Pal Singh
  
  PLOS One | May 2026
  
  Publication PDF DOI Project
- AI Research as a Continuous Clinical Service
  
  Yixi Xu, Rahul Dodhia, Juan M. Lavista Ferres, Bill Weeks
  
  Mayo Clinic Proceedings: Digital Health | December 2025
  
  Publication DOI PDF Project
- Liver MRI proton density fat fraction inference from contrast enhanced CT images using deep learning: A proof-of-concept study
  
  Md Nasir, Yixi Xu, Kyle Hasenstab, Alekhya Yechoor, Rahul Dodhia, Bill Weeks, Juan M. Lavista Ferres, Guilherme Moura Cunha
  
  PloS One | August 2025
  
  Publication PDF Project
- Cancer Detection in Breast MRI Screening via Explainable AI Anomaly Detection
  
  Felipe Oviedo, Anum S. Kazerouni, Philipp Liznerski, Yixi Xu, Michael Hirano, Robert A. Vandermeulen, Marius Kloft, Elyse Blum, Adam M. Alessio, Christopher I. Li, Bill Weeks, Rahul Dodhia, Juan M. Lavista Ferres, Habib Rahbar, Savannah C. Partridge
  
  Radiology | July 2025
  
  Publication PDF Project
- Rapid and accurate prediction of protein homo-oligomer symmetry using Seq2Symm
  
  Meghana Kshirsagar, Artur Meller, Ian R. Humphreys, Samuel Sledzieski, Yixi Xu, Rahul Dodhia, Eric Horvitz, Bonnie Berger, Gregory R. Bowman, Juan M. Lavista Ferres, David Baker, Minkyung Baek
  
  Nature Communications | February 2025
  
  Publication PDF Project
- Evaluating the Generalizability of Deep Learning Image Classification Algorithms to Detect Middle Ear Disease Using Otoscopy
  
  Al-Rahim Habib, Yixi Xu, Kris Bock, Shrestha Mohanty, Tina Sederholm, Bill Weeks, Rahul Dodhia, Juan M. Lavista Ferres, Chris Perry, Raymond Sacks, Narinder Singh
  
  Scientific Reports | April 2023
  
  Publication Project
- Automatic segmentation of prostate cancer metastases in PSMA PET/CT images using deep neural networks with weighted batch-wise dice loss
  
  Yixi Xu, Ivan Klyuzhin, Sara Harsini, Anthony Ortiz, Shun Zhang, François Bénard, Rahul Dodhia, Carlos F. Uribe, Arman Rahmim , Juan M. Lavista Ferres
  
  Computers in Biology and Medicine | April 2023
  
  Publication DOI Project Project
- A slice classification neural network for automated classification of axial PET/CT slices from a multi-centric lymphoma dataset
  
  Shadab Ahamed, Yixi Xu, Ingrid Bloise, Joo H. O., Carlos F. Uribe, Rahul Dodhia, Juan M. Lavista Ferres, Arman Rahmim
  
  Medical Imaging 2023 | April 2023
  
  Publication Project
- Identifying long-term effects of SARS-CoV-2 and their association with social determinants of health in a cohort of over one million COVID-19 survivors
  
  Sumit Mukherjee, Meghana Kshirsagar, Nicholas Becker, Yixi Xu, Bill Weeks, Shwetak Patel, Juan M. Lavista Ferres, Michael L. Jackson
  
  BMC Public Health | December 2022
  
  Publication PDF Project Project
- MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models
  
  Yixi Xu, Sumit Mukherjee, Xiyang Liu, Shruti Tople, Rahul Dodhia, Juan M. Lavista Ferres
  
  Transactions on Machine Learning Research (TMLR) | October 2022
  
  Publication Project Project
- Machine Learning-based Derivation and External Validation of a Tool to Predict Death and Development of Organ Failure in Hospitalized Patients with COVID-19
  
  Yixi Xu, Anusua Trivedi, Nicholas Becker, Marian Blazes, Juan M. Lavista Ferres, Dr. Aaron Lee, W Liles, Dr. Pavan Bhatraju
  
  Scientific Reports | October 2022
  
  Publication PDF Project Project
- Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features
  
  Ivan S. Klyuzhin, Juan M. Lavista Ferres, Yixi Xu, Anthony Ortiz, Ghassan Hamarneh, Arman Rahmim
  
  ScienceDirect | June 2022
  
  Publication Project
- Reimagining Leprosy Elimination with AI Analysis of a Combination of Skin Lesion Images with Demographic and Clinical Data
  
  Raquel R Barbieri, Yixi Xu, Lucy Setian, Paulo Thiago Souza-Santos, Anusua Trivedi, Jim Cristofono, Ricardo Bhering, Kevin White, Anna M Sales, Geralyn Miller, José Augusto C Nery, Michael Sharman, Richard Bumann, Shun Zhang, Mohamad Goldust, Euzenir N Sarno, Fareed Mirza, Arielle Cavaliero, Sander Timmer, Elena Bonfiglioli, Cairns Smith, David Scollard, Alexander A Navarini, Ann Aerts, Juan M. Lavista Ferres, Milton O Moraes
  
  Science Direct | January 2022
  
  Publication PDF Project Project
- Unsupervised Background Removal by Dual-Modality PET/CT Guidance: Application to PSMA Imaging of Metastases
  
  Ivan Klyuzhin, Yixi Xu, Sara Harsini, Anthony Ortiz, Carlos Uribe, Juan M. Lavista Ferres, Arman Rahmim
  
  Journal of Nuclear Medicine | May 2021
  
  Publication Project
- Comprehensive Evaluation and Insights into the Use of Deep Neural Networks to Detect and Quantify Lymphoma Lesions in PET/CT Images
  
  Shadab Ahamed, Yixi Xu, C. Gowdy, O. JooH., I. Bloise, Don Wilson, Patrick Martineau, François Bénard, F. Yousefirizi, Rahul Dodhia, Juan M. Lavista Ferres, Bill Weeks, Carlos F. Uribe, Arman Rahmim
  
  November 2023
  
  DOI Publication Github
- Towards an automated Segment Anything Model (SAM) for lesion segmentation in oncological PET/CT images
  
  S. Ahamed, Yixi Xu, Rahul Dodhia, Bill Weeks, Juan M. Lavista Ferres, A. Rahmim
  
  2023 IEEE Nuclear Science Symposium | December 2023
  
  Publication DOI Project
- Becoming Good at AI for Good
  
  Meghana Kshirsagar, Siyu Yang, Caleb Robinson, Shahrzad Gholami, Ivan Klyuzhin, Sumit Mukherjee, Md Nasir, Anthony Ortiz, Felipe Oviedo, Darren Tanner, Anusua Trivedi, Yixi Xu, Ming Zhong, Bistra Dilkina, Rahul Dodhia, Juan M. Lavista Ferres
  
  AAAI/ACM Conference on AI, Ethics, and Society (AIES'21) | April 2021
  
  Publication
- privGAN: Protecting GANs from membership inference attacks at low cost
  
  Sumit Mukherjee, Yixi Xu, Anusua Trivedi, Juan M. Lavista Ferres
  
  May 2020
  
  Under major revision at PETS
  
  Publication

Yixi Xu

Publications

Towards reliable use of artificial intelligence to classify otitis media using otoscopic images: Addressing bias and improving data quality

AI Research as a Continuous Clinical Service

Liver MRI proton density fat fraction inference from contrast enhanced CT images using deep learning: A proof-of-concept study

Cancer Detection in Breast MRI Screening via Explainable AI Anomaly Detection

Rapid and accurate prediction of protein homo-oligomer symmetry using Seq2Symm

Towards an automated Segment Anything Model (SAM) for lesion segmentation in oncological PET/CT images

Comprehensive Evaluation and Insights into the Use of Deep Neural Networks to Detect and Quantify Lymphoma Lesions in PET/CT Images

Evaluating the Generalizability of Deep Learning Image Classification Algorithms to Detect Middle Ear Disease Using Otoscopy

Automatic segmentation of prostate cancer metastases in PSMA PET/CT images using deep neural networks with weighted batch-wise dice loss

A slice classification neural network for automated classification of axial PET/CT slices from a multi-centric lymphoma dataset

Identifying long-term effects of SARS-CoV-2 and their association with social determinants of health in a cohort of over one million COVID-19 survivors

MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models

Machine Learning-based Derivation and External Validation of a Tool to Predict Death and Development of Organ Failure in Hospitalized Patients with COVID-19

Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features

Reimagining Leprosy Elimination with AI Analysis of a Combination of Skin Lesion Images with Demographic and Clinical Data

Unsupervised Background Removal by Dual-Modality PET/CT Guidance: Application to PSMA Imaging of Metastases

Becoming Good at AI for Good

privGAN: Protecting GANs from membership inference attacks at low cost

Towards reliable use of artificial intelligence to classify otitis media using otoscopic images: Addressing bias and improving data quality

AI Research as a Continuous Clinical Service

Liver MRI proton density fat fraction inference from contrast enhanced CT images using deep learning: A proof-of-concept study

Cancer Detection in Breast MRI Screening via Explainable AI Anomaly Detection

Rapid and accurate prediction of protein homo-oligomer symmetry using Seq2Symm

Towards an automated Segment Anything Model (SAM) for lesion segmentation in oncological PET/CT images

Comprehensive Evaluation and Insights into the Use of Deep Neural Networks to Detect and Quantify Lymphoma Lesions in PET/CT Images

Evaluating the Generalizability of Deep Learning Image Classification Algorithms to Detect Middle Ear Disease Using Otoscopy

Automatic segmentation of prostate cancer metastases in PSMA PET/CT images using deep neural networks with weighted batch-wise dice loss

A slice classification neural network for automated classification of axial PET/CT slices from a multi-centric lymphoma dataset

MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models

Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features

Unsupervised Background Removal by Dual-Modality PET/CT Guidance: Application to PSMA Imaging of Metastases

Becoming Good at AI for Good

privGAN: Protecting GANs from membership inference attacks at low cost

Towards reliable use of artificial intelligence to classify otitis media using otoscopic images: Addressing bias and improving data quality

Liver MRI proton density fat fraction inference from contrast enhanced CT images using deep learning: A proof-of-concept study

Cancer Detection in Breast MRI Screening via Explainable AI Anomaly Detection

Rapid and accurate prediction of protein homo-oligomer symmetry using Seq2Symm

Towards an automated Segment Anything Model (SAM) for lesion segmentation in oncological PET/CT images

Comprehensive Evaluation and Insights into the Use of Deep Neural Networks to Detect and Quantify Lymphoma Lesions in PET/CT Images

Evaluating the Generalizability of Deep Learning Image Classification Algorithms to Detect Middle Ear Disease Using Otoscopy

Automatic segmentation of prostate cancer metastases in PSMA PET/CT images using deep neural networks with weighted batch-wise dice loss

A slice classification neural network for automated classification of axial PET/CT slices from a multi-centric lymphoma dataset

Identifying long-term effects of SARS-CoV-2 and their association with social determinants of health in a cohort of over one million COVID-19 survivors

Machine Learning-based Derivation and External Validation of a Tool to Predict Death and Development of Organ Failure in Hospitalized Patients with COVID-19

Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features

Reimagining Leprosy Elimination with AI Analysis of a Combination of Skin Lesion Images with Demographic and Clinical Data

Unsupervised Background Removal by Dual-Modality PET/CT Guidance: Application to PSMA Imaging of Metastases

Comprehensive Evaluation and Insights into the Use of Deep Neural Networks to Detect and Quantify Lymphoma Lesions in PET/CT Images

privGAN: Protecting GANs from membership inference attacks at low cost

MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models

privGAN: Protecting GANs from membership inference attacks at low cost

Towards reliable use of artificial intelligence to classify otitis media using otoscopic images: Addressing bias and improving data quality

AI Research as a Continuous Clinical Service

Liver MRI proton density fat fraction inference from contrast enhanced CT images using deep learning: A proof-of-concept study

Cancer Detection in Breast MRI Screening via Explainable AI Anomaly Detection

Rapid and accurate prediction of protein homo-oligomer symmetry using Seq2Symm

Evaluating the Generalizability of Deep Learning Image Classification Algorithms to Detect Middle Ear Disease Using Otoscopy

Automatic segmentation of prostate cancer metastases in PSMA PET/CT images using deep neural networks with weighted batch-wise dice loss

A slice classification neural network for automated classification of axial PET/CT slices from a multi-centric lymphoma dataset

Identifying long-term effects of SARS-CoV-2 and their association with social determinants of health in a cohort of over one million COVID-19 survivors

MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models

Machine Learning-based Derivation and External Validation of a Tool to Predict Death and Development of Organ Failure in Hospitalized Patients with COVID-19

Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features

Reimagining Leprosy Elimination with AI Analysis of a Combination of Skin Lesion Images with Demographic and Clinical Data

Unsupervised Background Removal by Dual-Modality PET/CT Guidance: Application to PSMA Imaging of Metastases

Comprehensive Evaluation and Insights into the Use of Deep Neural Networks to Detect and Quantify Lymphoma Lesions in PET/CT Images

Towards an automated Segment Anything Model (SAM) for lesion segmentation in oncological PET/CT images

Becoming Good at AI for Good

privGAN: Protecting GANs from membership inference attacks at low cost