H. Trivedi

发表

A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18F-FDG PET of the Brain.

Yiming Ding, D. Hadley, J. H. Sohn, 2019, Radiology.

Fusion of Imaging and Non-Imaging Data for Disease Trajectory Prediction for COVID-19 Patients

L. Celi, H. Trivedi, D. Rubin, 2021, medRxiv.

Multiparametric 3T prostate magnetic resonance imaging to detect cancer: histopathological correlation using prostatectomy specimens processed in customized magnetic resonance imaging based molds.

Baris Turkbey, Marcelino Bernardo, Yuxi Pang, 2011, The Journal of urology.

Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms

Berkman Sahiner, Jaime S. Cardoso, Thomas Yu, 2020, JAMA network open.

A DICOM Framework for Machine Learning and Processing Pipelines Against Real-time Radiology Images

Saptarshi Purkayastha, Ashish Sharma, Nabile Safdar, 2020, Journal of Digital Imaging.

Multi-Institutional Validation of a Mammography-Based Breast Cancer Risk Model

Renato F Caron, R. Barzilay, C. Lehman, 2021, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

A Systematic Review of ‘Fair’ AI Model Development for Image Classification and Prediction

L. Celi, H. Trivedi, J. Gichoya, 2022, Journal of Medical and Biological Engineering.

Patient-specific COVID-19 resource utilization prediction using fusion AI model

L. Celi, H. Trivedi, S. Purkayastha, 2021, npj Digital Medicine.

Multiparametric 3T Prostate MR Imaging to Detect Cancer: Histopathologic Correlation Using Prostatectomy Specimens Processed in Customized MRI-Based Molds

P. Choyke, M. Merino, H. Trivedi, 2017 .

P. Choyke, H. Trivedi, P. Pinto, 2012, BJU international.

Overview of Noninterpretive Artificial Intelligence Models for Safety, Quality, Workflow, and Education Applications in Radiology Practice.

Nabile M. Safdar, H. Trivedi, Elizabeth A. Krupinski, 2022, Radiology. Artificial intelligence.

Advances in Prediction of Readmission Rates Using Long Term Short Term Memory Networks on Healthcare Insurance Data

H. Trivedi, J. Gichoya, I. Banerjee, 2022, ArXiv.

AI recognition of patient race in medical imaging: a modelling study

John L. Burns, Brandon J Price, M. Ghassemi, 2022, The Lancet. Digital health.

Early Diagnosis of Chronic Obstructive Pulmonary Disease from Chest X-Rays using Transfer Learning and Fusion Strategies

L. Celi, H. Trivedi, Po-Chih Kuo, 2022, ArXiv.

Systematic Review of Generative Adversarial Networks (GANs) for Medical Image Classification and Segmentation

H. Trivedi, J. Gichoya, I. Banerjee, 2022, Journal of Digital Imaging.

Evaluation of blood donor deferral causes: a tertiary-care center-based study -

H. Trivedi, K. N. Desai, A. Agnihotri, 2015 .

Automatic Classification of Cancer Pathology Reports: A Systematic Review

H. Trivedi, J. Gichoya, I. Banerjee, 2022, Journal of pathology informatics.

Optimizing risk-based breast cancer screening policies with reinforcement learning

R. Barzilay, C. Lehman, H. Trivedi, 2021, Nature Medicine.

Automatic Labeling of Special Diagnostic Mammography Views from Images and DICOM Headers

Dexter Hadley, Maryam Panahiazar, Youngho Seo, 2018, Journal of Digital Imaging.

OSCARS: An Outlier-Sensitive Content-Based Radiography Retrieval System

H. Trivedi, S. Purkayastha, J. Gichoya, 2022, ICMR.

Comparison of clinical and imaging features in succinate dehydrogenase-positive versus sporadic paragangliomas.

H. Trivedi, A. Venkatesan, E. Kebebew, 2011, Surgery.

Patient-specific COVID-19 resource utilization prediction using fusion AI model

L. Celi, H. Trivedi, S. Purkayastha, 2021, npj Digital Medicine.

AI recognition of patient race in medical imaging: a modelling study pdf

Saptarshi Purkayastha, Marzyeh Ghassemi, Leo Anthony Celi, 2021, The Lancet. Digital health.

SCU-Net: A deep learning method for segmentation and quantification of breast arterial calcifications on mammograms

H. Trivedi, I. Pan, W. C. O'Neill, 2021, medRxiv.

The EMory BrEast imaging Dataset (EMBED): A Racially Diverse, Granular Dataset of 3.4 Million Screening and Diagnostic Mammographic Images.

H. Trivedi, M. Newell, A. Bhimireddy, 2023, Radiology. Artificial intelligence.

Current Clinical Applications of Artificial Intelligence in Radiology and Their Best Supporting Evidence.

Saptarshi Purkayastha, Imon Banerjee, Elizabeth Krupinski, 2020, Journal of the American College of Radiology : JACR.

Automatic Determination of the Need for Intravenous Contrast in Musculoskeletal MRI Examinations Using IBM Watson’s Natural Language Processing Algorithm

Joseph Mesterhazy, Jae Ho Sohn, Benjamin Laguna, 2018, Journal of Digital Imaging.

Anatomic thermochromic tissue-mimicking phantom of the lumbar spine for pre-clinical evaluation of MR-guided focused ultrasound (MRgFUS) ablation of the facet joint

C. Diederich, V. Rieke, H. Trivedi, 2021, International Journal of Hyperthermia.

Magnetic resonance imaging (MRI)‐guided transurethral ultrasound therapy of the prostate: a preclinical study with radiological and pathological correlation using customised MRI‐based moulds

P. Choyke, W. Linehan, G. Ehnholm, 2013, BJU international.

The State of Radiology AI: Considerations for Purchase Decisions and Current Market Offerings.

Nabile M. Safdar, E. Krupinski, H. Trivedi, 2020, Radiology. Artificial intelligence.

MedShift: identifying shift data for medical dataset curation pdf

Saptarshi Purkayastha, Imon Banerjee, Judy Wawira Gichoya, 2021, ArXiv.

Use of patient-specific MRI-based prostate mold for validation of multiparametric MRI in localization of prostate cancer.

Baris Turkbey, Peter L. Choyke, Bradford J. Wood, 2012, Urology.

Ethics of large language models in medicine and medical research.

L. Celi, H. Trivedi, S. Purkayastha, 2023, The Lancet. Digital health.

The EMory BrEast imaging Dataset (EMBED): A Racially Diverse, Granular Dataset of 3.5M Screening and Diagnostic Mammograms

H. Trivedi, M. Newell, A. Bhimireddy, 2022, ArXiv.

Automatic Localization and Brand Detection of Cervical Spine Hardware on Radiographs Using Weakly Supervised Machine Learning.

M. Ghassemi, H. Trivedi, J. Gichoya, 2022, Radiology. Artificial intelligence.

Artificial Intelligence in Quality Improvement: Reviewing Uses of Artificial Intelligence in Noninterpretative Processes from Clinical Decision Support to Education and Feedback.

Nabile M. Safdar, Marta E Heilbrun, Neil Bhatia, 2020, Journal of the American College of Radiology : JACR.

Fusion of imaging and non-imaging data for disease trajectory prediction for coronavirus disease 2019 patients

L. Celi, D. Rubin, H. Trivedi, 2023, Journal of medical imaging.

A DICOM Framework for Machine Learning and Processing Pipelines Against Real-time Radiology Images

Saptarshi Purkayastha, Pradeeban Kathiravelu, Imon Banerjee, 2020, Journal of Digital Imaging.

PathologyBERT - Pre-trained Vs. A New Transformer Language Model for Pathology Domain

H. Trivedi, I. Banerjee, Geoffrey H. Smith, 2022, AMIA.

Multiple hereditary exostoses: A pseudoaneurysm masquerading as tumor.

H. Trivedi, T. Link, R. O'Donnell, 2016, Journal of radiology case reports.

Machine Learning Methods to Predict Survival in Patients Following Traumatic Aortic Injury

H. Trivedi, J. Gichoya, I. Banerjee, 2021, medRxiv.

Graph-Based Fusion of Imaging and Non-Imaging Data for Disease Trajectory Prediction

L. Celi, H. Trivedi, D. Rubin, 2023, International IEEE/EMBS Conference on Neural Engineering.

Graph-based Fusion Modeling and Explanation for Disease Trajectory Prediction

L. Celi, H. Trivedi, D. Rubin, 2022, medRxiv.

Impact of multi-source data augmentation on performance of convolutional neural networks for abnormality classification in mammography

H. Trivedi, J. Gichoya, I. Banerjee, 2023, Frontiers in radiology.

MedShift: Automated Identification of Shift Data for Medical Image Dataset Curation

H. Trivedi, S. Purkayastha, J. Gichoya, 2023, IEEE Journal of Biomedical and Health Informatics.

A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18F-FDG PET of the Brain.

Yiming Ding, D. Hadley, K. Zalocusky, 2019, Radiology.

Multi-Label Medical Image Retrieval Via Learning Multi-Class Similarity

H. Trivedi, S. Purkayastha, J. Gichoya, 2022, SSRN Electronic Journal.

Was there COVID-19 back in 2012? Challenge for AI in Diagnosis with Similar Indications pdf

Saptarshi Purkayastha, Judy W. Gichoya, Jiwoong Jeong, 2020, ArXiv.

Large Scale Semi-Automated Labeling of Routine Free-Text Clinical Records for Deep Learning

Dexter Hadley, Maryam Panahiazar, Bonnie Joe, 2018, Journal of Digital Imaging.

Query bot for retrieving patients’ clinical history: A COVID-19 use-case

H. Trivedi, J. Gichoya, I. Banerjee, 2021, Journal of Biomedical Informatics.

Visualizing Scanner Utilization From MRI Metadata and Clinical Data

Nabile M. Safdar, H. Trivedi, A. Bhimireddy, 2023, Computer.

Failures Hiding in Success for Artificial Intelligence in Radiology.

H. Trivedi, S. Purkayastha, J. Gichoya, 2021, Journal of the American College of Radiology : JACR.

Benchmarking bias: Expanding clinical AI model card to incorporate bias reporting of social and non-social factors

H. Trivedi, J. Gichoya, L. Seyyed-Kalantari, 2023, ArXiv.

AI Education for Fourth-Year Medical Students: Two-Year Experience of a Web-Based, Self-Guided Curriculum and Mixed Methods Study

H. Trivedi, S. Purkayastha, J. Gichoya, 2023, JMIR medical education.

Opportunistic screening for coronary artery calcium deposition using chest radiographs - a multi-objective models with multi-modal data fusion

H. Trivedi, Milagros Pereyra, Chieh-Ju Chao, 2024, medRxiv.