Submissions from 2024
Colorectal Cancer Detection via Metabolites and Machine Learning., Rachel Yang, Igor F Tsigelny, Santosh Kesari, and Valentina L Kouznetsova
A framework towards digital twins for type 2 diabetes., Yue Zhang, Guangrong Qin, Boris Aguilar, Noa Rappaport, James T Yurkovich, Lance Pflieger, Sui Huang, Leroy Hood, and Ilya Shmulevich
Submissions from 2023
Deep Learning Applications Using H&E Images Improve Clinical Sequencing Workflows, J Abel, Brian Piening, Carlo Bifulco, and See full list of authors in comments
Sociodemographic determinants of oral anticoagulant prescription in patients with atrial fibrillations: findings from the PINNACLE registry using machine learning., Zahra Azizi, Andrew T Ward, Donghyun J Lee, Sanchit S Gad, Kanchan Bhasin, Robert J Beetel, Tiago Ferreira, Sushant Shankar, John S Rumsfeld, Robert A Harrington, Salim S Virani, Tyler J Gluckman, Rajesh Dash, and Fatima Rodriguez
Patient clusters identified by machine learning from a pooled analysis of the clinical development programme of secukinumab in psoriatic arthritis, ankylosing spondylitis and psoriatic arthritis with axial manifestations., Xenofon Baraliakos, Effie Pournara, Laura C Coates, Philip Mease, Samad S Jahandideh, and Dafna D Gladman
Evolution of the digital operating room: the place of video technology in surgery., Samy Cheikh Youssef, Kaled Haram, Jonathan Noël, Vipul Patel, James Porter, Prokar Dasgupta, and Nadine Hachach-Haram
Two-Stage Deep-Learning Classifier for Diagnostics of Lung Cancer Using Metabolites., Ashvin Choudhary, Jianpeng Yu, Valentina L Kouznetsova, Santosh Kesari, and Igor F Tsigelny
Novel Technique of Head-Mounted Augmented Reality-Assisted Endovascular Neurosurgery: Proof of Concept on a Flow Model., Matias Costa, Clifford A Pierre, Mohammed Basamh, Juan Vivanco-Suarez, Matias Baldoncini, and Stephen Monteith
An approach for collaborative development of a federated biomedical knowledge graph-based question-answering system: Question-of-the-Month challenges., Karamarie Fecho, Chris Bizon, Tursynay Issabekova, Sierra Moxon, Anne E Thessen, Shervin Abdollahi, Sergio E Baranzini, Basazin Belhu, William E Byrd, Lawrence Chung, Andrew Crouse, Marc P Duby, Stephen Ferguson, Aleksandra Foksinska, Laura Forero, Jennifer Friedman, Vicki Gardner, Gwênlyn Glusman, Jennifer Hadlock, Kristina Hanspers, Eugene Hinderer, Charlotte Hobbs, Gregory Hyde, Sui Huang, David Koslicki, Philip Mease, Sandrine Muller, Christopher J Mungall, Stephen A Ramsey, Jared Roach, Irit Rubin, Shepherd H Schurman, Anath Shalev, Brett Smith, Karthik Soman, Sarah Stemann, Andrew I Su, Casey Ta, Paul B Watkins, Mark D Williams, Chunlei Wu, Colleen H Xu, and Biomedical Data Translator Consortium
National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in Imaging Artificial Intelligence., Andrey Fedorov, William J R Longabaugh, David Pot, David A Clunie, Steven D Pieper, David L Gibbs, Christopher Bridge, Markus D Herrmann, André Homeyer, Rob Lewis, Hugo J W L Aerts, Deepa Krishnaswamy, Vamsi Krishna Thiriveedhi, Cosmin Ciausu, Daniela P Schacherer, Dennis Bontempi, Todd Pihl, Ulrike Wagner, Keyvan Farahani, Erika Kim, and Ron Kikinis
Retrospective comparison of traditional and artificial intelligence-based heart failure phenotyping in a US health system to enable real-world evidence., Arthur Reshad Garan, Keri L Monda, Ricardo E Dent-Acosta, Daniel J Riskin, and Tyler J Gluckman
What We Owe Those Who Chat Woe: A Relational Lens for Mental Health Apps., Anita Ho and Joseph Perry
A Practical Guide to Relugolix: Early Experience With Oral Androgen Deprivation Therapy., Saro Kasparian, Oren Wei, Ni-Chun Tsai, Joycelynne Palmer, Sumanta Pal, Yung Lyou, and Tanya Dorff
Generating Insights from Catholic Social Teaching: Ethical Guidelines for Artificial Intelligence in Health Care Ministries, Nicholas Kockler
Diagnostics of Thyroid Cancer Using Machine Learning and Metabolomics., Alyssa Kuang, Valentina L Kouznetsova, Santosh Kesari, and Igor F Tsigelny
Toward an Integrated Machine Learning Model of a Proteomics Experiment., Benjamin A Neely, Viktoria Dorfer, Lennart Martens, Isabell Bludau, Robbin Bouwmeester, Sven Degroeve, Eric W Deutsch, Siegfried Gessulat, Lukas Käll, Pawel Palczynski, Samuel H Payne, Tobias Greisager Rehfeldt, Tobias Schmidt, Veit Schwämmle, Julian Uszkoreit, Juan Antonio Vizcaíno, Mathias Wilhelm, and Magnus Palmblad
Framework and metrics for the clinical use and implementation of artificial intelligence algorithms into endoscopy practice: recommendations from the American Society for Gastrointestinal Endoscopy Artificial Intelligence Task Force., Sravanthi Parasa, Alessandro Repici, Tyler Berzin, Cadman Leggett, Seth A Gross, and Prateek Sharma
Disease Assessments in Patients with Glioblastoma., Kester A Phillips, David O Kamson, and David Schiff
Advanced artificial intelligence-guided hemodynamic management within cardiac enhanced recovery after surgery pathways: A multi-institution review., V Seenu Reddy, David M Stout, Robert Fletcher, Andrew Barksdale, Manesh Parikshak, Chanice Johns, and Marc Gerdisch
ChatGPT and large language models in gastroenterology., Prateek Sharma and Sravanthi Parasa
Phenotyping sub-populations of heart failure patients based on clinical and social determinants of health using unsupervised machine learning models, Kateri Spinelli, HF Li, Jacob Abraham, X Huang, and See full list of authors in comments
Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Research Diversity (AIM-AHEAD), Katherine Tuttle, Radica Alicic, Cami Jones, Lindsey Kornowske, Kenn Daratha, and See full list of authors in comments
Robot-assisted partial nephrectomy for complex renal tumors: Analysis of a large multi-institutional database., Burak Ucpinar, Jordan Miller Rich, Kennedy E Okhawere, Shirin Razdan, Osama Zaytoun, Laura Zuluaga, Indu Saini, Michael D Stifelman, Ronney Abaza, Daniel D Eun, Akshay Bhandari, Ashok K Hemal, James Porter, Simone Crivellero, Ahmed Mansour, Phillip M Pierorazio, and Ketan K Badani
Clinical Course of Patients in Cardiogenic Shock Stratified by Phenotype., Elric Zweck, Manreet Kanwar, Song Li, Shashank S Sinha, A Reshad Garan, Jaime Hernandez-Montfort, Yijing Zhang, Borui Li, Paulina Baca, Fatou Dieng, Neil M Harwani, Jacob Abraham, Gavin Hickey, Sandeep Nathan, Detlef Wencker, Shelley Hall, Andrew Schwartzman, Wissam Khalife, Claudius Mahr, Ju H Kim, Esther Vorovich, Evan H Whitehead, Vanessa Blumer, Ralf Westenfeld, Daniel Burkhoff, and Navin K Kapur
Submissions from 2022
Imputing Missing Observations with Time Sliced Synthetic Minority Oversampling Technique, Andrew M Baumgartner, Sevda Molani, Qi Wei, and Jennifer J Hadlock
On the Criticality of Adaptive Boolean Network Robots., Michele Braccini, Andrea Roli, Edoardo Barbieri, and Stuart A Kauffman
Machine learning in clinical diagnosis, prognostication, and management of acute traumatic spinal cord injury (SCI): A systematic review., Nicholas Dietz, Vaitheesh Jaganathan, Victoria Alkin, Jersey Mettille, Maxwell Boakye, and Doniel Drazin
On evaluation metrics for medical applications of artificial intelligence., Steven A Hicks, Inga Strümke, Vajira Thambawita, Malek Hammou, Michael A Riegler, Pål Halvorsen, and Sravanthi Parasa
Using machine learning to predict internal rotation after anatomic and reverse total shoulder arthroplasty., Vikas Kumar, Bradley S Schoch, Christine Allen, Steve Overman, Ankur Teredesai, William Aibinder, Moby Parsons, Jonathan Watling, Jia-Wei Kevin Ko, Bruno Gobbato, Thomas Throckmorton, Howard Routman, and Christopher Roche
Artificial intelligence-enabled electrocardiography identifies severe dyscalcemias and has prognostic value., Chin Lin, Chien-Chou Chen, Tom Chau, Chin-Sheng Lin, Shi-Hung Tsai, Ding-Jie Lee, Chia-Cheng Lee, Hung-Sheng Shang, and Shih-Hua Lin
Personal Dense Dynamic Data Clouds Connect Systems Biomedicine to Scientific Wellness., Gilbert S Omenn, Andrew T Magis, Nathan D Price, and Leroy Hood
A Functional Module States Framework Reveals Transcriptional States for Drug and Target Prediction., Guangrong Qin, Theo A Knijnenburg, David L Gibbs, Russell Moser, Raymond J Monnat, Christopher J Kemp, and Ilya Shmulevich
Exploring approaches for predictive cancer patient digital twins: Opportunities for collaboration and innovation., Eric A Stahlberg, Mohamed Abdel-Rahman, Boris Aguilar, Alireza Asadpoure, Robert A Beckman, Lynn L Borkon, Jeffrey N Bryan, Colleen M Cebulla, Young Hwan Chang, Ansu Chatterjee, Jun Deng, Sepideh Dolatshahi, Olivier Gevaert, Emily J Greenspan, Wenrui Hao, Tina Hernandez-Boussard, Pamela R Jackson, Marieke Kuijjer, Adrian Lee, Paul Macklin, Subha Madhavan, Matthew D McCoy, Navid Mohammad Mirzaei, Talayeh Razzaghi, Heber L Rocha, Leili Shahriyari, Ilya Shmulevich, Daniel G Stover, Yi Sun, Tanveer Syeda-Mahmood, Jinhua Wang, Qi Wang, and Ioannis Zervantonakis
SinGAN-Seg: Synthetic training data generation for medical image segmentation., Vajira Thambawita, Pegah Salehi, Sajad Amouei Sheshkal, Steven A Hicks, Hugo L Hammer, Sravanthi Parasa, Thomas de Lange, Pål Halvorsen, and Michael A Riegler
Submissions from 2021
Identification of successful cerebral reperfusions (mTICI ≥2b) using an artificial intelligence strategy., Gabriel Neves, Pranav Warman, Tulio Bueso, Walter Duarte-Celada, and Thomas Windisch
Mars Shot for Nuclear Medicine, Molecular Imaging, and Molecularly Targeted Radiopharmaceutical Therapy., Richard L Wahl, Panithaya Chareonthaitawee, Bonnie Clarke, Alexander Drzezga, Liza Lindenberg, Arman Rahmim, James Thackeray, Gary A Ulaner, Wolfgang Weber, Katherine Zukotynski, and John Sunderland
Submissions from 2020
In Reply to the Letter to the Editor Regarding "Investigating Risk Factors and Predicting Complications in Deep Brain Stimulation Surgery with Machine Learning Algorithms"., Quinlan D Buchlak, Farrokh Farrokhi, Matt Sikora, Nazanin Esmaili, Maria Marsans, Pamela McLeod, Jamie Mark, Emily J Cox, Christine Bennett, and Jonathan Carlson
Investigating Risk Factors and Predicting Complications in Deep Brain Stimulation Surgery with Machine Learning Algorithms., Farrokh Farrokhi, Quinlan D Buchlak, Matt Sikora, Nazanin Esmaili, Maria Marsans, Pamela McLeod, Jamie Mark, Emily J Cox, Christine Bennett, and Jonathan Carlson
Artificial Intelligence in Cardiology., Dipti Itchhaporia
Artificial Intelligence for Rapid Meta-Analysis: Case Study on Ocular Toxicity of Hydroxychloroquine., Matthew Michelson, Tiffany Chow, Neil A Martin, Mike Ross, Amelia Tee Qiao Ying, and Steven Minton
Advancing human health in the decade ahead: pregnancy as a key window for discovery: A Burroughs Wellcome Fund Pregnancy Think Tank., Yoel Sadovsky, Sam Mesiano, Graham J Burton, Michelle Lampl, Jeffrey C Murray, Rachel M Freathy, Anita Mahadevan-Jansen, Ashley Moffett, Nathan D Price, Paul H Wise, Derek E Wildman, Ralph Snyderman, Nigel Paneth, John Anthony Capra, Marcelo A Nobrega, Yaacov Barak, and Louis J Muglia
Submissions from 2019
Epigenetic Classifiers for Precision Diagnosis of Brain Tumors., Javier I Orozco, Ayla O Manughian-Peter, Matthew P Salomon, and Diego M Marzese
Artificial Intelligence and Machine Learning in Cardiology., R Jeffrey Westcott and James E Tcheng
Books from 2018
Open-source digital image analysis of whole-slide multiplex immunohistochemistry, Nikhil Lonberg, Carmen Ballesteros-Merino, Shawn Jensen, and Bernard A Fox
Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images., Joel Saltz, Rajarsi Gupta, Le Hou, Tahsin Kurc, Pankaj Singh, Vu Nguyen, Dimitris Samaras, Kenneth R Shroyer, Tianhao Zhao, Rebecca Batiste, John Van Arnam, Ilya Shmulevich, Arvind U K Rao, Alexander J Lazar, Ashish Sharma, and Vésteinn Thorsson
Submissions from 2017
Diagnosis of major depressive disorder by combining multimodal information from heart rate dynamics and serum proteomics using machine-learning algorithm., Eun Young Kim, Min Young Lee, Se Hyun Kim, Kyooseob Ha, Kwang Pyo Kim, and Yong Min Ahn
