Artificial Intelligence, Public Trust, and Public Health
Posted on byAs a data-driven agency, CDC has always had highly skilled statisticians and data scientists. As part of the Data Modernization Initiative, CDC is supporting strategic innovations in data science using artificial intelligence and machine learning (Ai/ML). Ai/ML is the practice of using mathematics with computers to learn from a wide range of data and make predictions about the health of populations. By using Ai/ML, CDC can maximize insights from data to improve disease detection, mitigation, and elimination. Ai/ML applications could support public health surveillance, research and, ultimately, decision making, ushering a new era of precision public health.
Here, we provide a quick overview of how CDC scientists are using Ai/ML in public health surveillance and research. We sought to answer three questions:
- What topics have been covered by publications?
- How frequently is open-source software used?
- How often do authors make their algorithms public?
The presence of multiple topics would indicate wide use of Ai/ML across CDC. The use of open source software allows anyone to duplicate methods without having to pay fees for specialized software. By making algorithms publicly available, researchers avoid using what may be perceived by outsiders as a black box; this can be particularly powerful in improving transparency when combined with existing federal efforts to make data more readily available to the public.
First, we used 19 Ai/ML-related keyworks to cast a wide net in searching PubMed. Next, we reviewed abstracts to exclude publications that were not related to Ai/ML or did not have a CDC author. We also sent out request through multiple listservs requesting additional information from CDC researchers the use of Ai/ML. Finally, we reviewed about 200 publications. A total of 85 publications were selected for final inclusion. To be included, the publication had at least one CDC author and use/review Ai/ML. Results of our brief literature investigation are available below. Our review explored what type of Ai/ML was used (e.g., NLP, classification, computer vision), whether open source software was used (e.g., R, Python), types of models used (e.g., convolutional neural network, super learner, support vector machine), whether statistical algorithm used was made public (e.g., on GitHub), topic of research (e.g., Zika, obesity), and all the elements typically made available by PubMed (e.g., PMID, title, abstract).
The 85 CDC publications cover a vast array of topics, including: human genetics; autism; injury at work; cancer; diabetes; Hepatitis C; influenza; nanomaterials; obesity; opioids; electronic health records; streptococcus; vaccines; and many other topics. Although publications start in 2003, about half of publications were published between 2017 and 2020. Notably more than half of the publications make use of open-source software to implement Ai/ML in the analysis. However, only one-in-six (~16%) authors make their detailed Ai/ML algorithms publicly available. The use of open source software and making algorithms publicly available could help promote transparency.
There are two examples of clear standouts when it comes to using open source software and making algorithms publicly available. Publications that include Dr. Scott Lee (at the Center for Surveillance, Epidemiology, and Laboratory Services) or Dr. Wei Yu (at the Office of Genomics and Precision Public Health) make a great effort to ensure readers understand how their analysis can be replicated using open source software and archived algorithms. By making detailed algorithms publicly available, authors advance transparency in research and ensure invested resources are maximized. For example, a recent CDC publication investigated how state-level forecasting of influenza could be improved by using Ai/ML. The authors archived their open source code here. In the GitHub depository, readers are given step-by-step instructions on how to apply the Ai/ML algorithm to replicate study findings.
This analysis shows CDC’s increasing commitment to using Ai/ML for a vast array of topics. Authors sometimes use open-source software, but less often make algorithms publicly available. Continued efforts are needed to promote data availability and transparency of methods. Advancing more precision in public health research, policy, and programs will increasingly require making use of emerging Ai/ML technologies in response to public health issues.
* CDC publications include those with one or more authors from the Centers for Disease Control and Prevention or the Agency for Toxic Substances and Disease Registry
PubMed ID | Title | Authors |
---|---|---|
14700412 | Electronic interpretation of chest radiograph reports to detect central venous catheters | William E Trick, Wendy W Chapman, Mary F Wisniewski, Brian J Peterson, Steven L Solomon, Robert A Weinstein |
15217815 | Standardization and denoising algorithms for mass spectra to classify whole-organism bacterial specimens | Glen A Satten, Somnath Datta, Hercules Moura, Adrian R Woolfitt, Maria da G Carvalho, George M Carlone, Barun K De, Antonis Pavlopoulos, John R Barr |
16606998 | Predicting density of Ixodes pacificus nymphs in dense woodlands in Mendocino County, California, based on geographic information systems and remote sensing versus field-derived data | Rebecca J Eisen, Lars Eisen, Robert S Lane |
16610958 | Allostatic load is associated with symptoms in chronic fatigue syndrome patients | Benjamin N Goertzel, Cassio Pennachin, Lucio de Souza Coelho, Elizabeth M Maloney, James F Jones, Brian Gurbaxani |
16899605 | Predicting cancer drug response by proteomic profiling | Yan Ma, Zhenyu Ding, Yong Qian, Xianglin Shi, Vince Castranova, E James Harner, Lan Guo |
17109381 | Discrimination of intact mycobacteria at the strain level: a combined MALDI-TOF MS and biostatistical analysis | Justin M Hettick, Michael L Kashon, James E Slaven, Yan Ma, Janet P Simpson, Paul D Siegel, Gerald N Mazurek, David N Weissman |
17238741 | Concept negation in free text components of vaccine safety reports | Herman Tolentino, Michael Matters, Wikke Walop, Barbara Law, Wesley Tong, Fang Liu, Paul Fontelo, Katrin Kohl, Daniel Payne |
17295907 | A UMLS-based spell checker for natural language processing in vaccine safety | Herman D Tolentino, Michael D Matters, Wikke Walop, Barbara Law, Wesley Tong, Fang Liu, Paul Fontelo, Katrin Kohl, Daniel C Payne |
17654333 | A new descriptor selection scheme for SVM in unbalanced class problem: a case study using skin sensitisation dataset | S Li, A Fedorowicz, M E Andrew |
17996092 | An open source infrastructure for managing knowledge and finding potential collaborators in a domain-specific subset of PubMed, with an example from human genome epidemiology | Wei Yu, Ajay Yesupriya, Anja Wulf, Junfeng Qu, Muin J Khoury, Marta Gwinn |
18430222 | GAPscreener: an automatic tool for screening human genetic association literature in PubMed using the support vector machine technique | Wei Yu, Melinda Clyne, Siobhan M Dolan, Ajay Yesupriya, Anja Wulf, Tiebin Liu, Muin J Khoury, Marta Gwinn |
18537829 | MALDI-TOF mass spectrometry as a tool for differentiation of invasive and noninvasive Streptococcus pyogenes isolates | Hercules Moura, Adrian R Woolfitt, Maria G Carvalho, Antonis Pavlopoulos, Lucia M Teixeira, Glen A Satten, John R Barr |
18628290 | Artificial neural network for prediction of antigenic activity for a major conformational epitope in the hepatitis C virus NS3 protein | James Lara, Robert M Wohlhueter, Zoya Dimitrova, Yury E Khudyakov |
18708515 | Differentiation of Streptococcus pneumoniae conjunctivitis outbreak isolates by matrix-assisted laser desorption ionization-time of flight mass spectrometry | Yulanda M Williamson, Hercules Moura, Adrian R Woolfitt, James L Pirkle, John R Barr, Maria Da Gloria Carvalho, Edwin P Ades, George M Carlone, Jacquelyn S Sampson |
19390102 | A rule-based approach for identifying obesity and its comorbidities in medical discharge summaries | Ninad K Mishra, David M Cummo, James J Arnzen, Jason Bonander |
19864262 | A rule-based approach for identifying obesity and its comorbidities in medical discharge summaries | Ninad K Mishra, David M Cummo, James J Arnzen, Jason Bonander |
20307319 | Application of support vector machine modeling for prediction of common diseases: the case of diabetes and pre-diabetes | Wei Yu, Tiebin Liu, Rodolfo Valdez, Marta Gwinn, Muin J Khoury |
20942945 | Quadratic variance models for adaptively preprocessing SELDI-TOF mass spectrometry data | Vincent A Emanuele 2nd, Brian M Gurbaxani |
21772787 | Emerging vaccine informatics | Yongqun He, Rino Rappuoli, Anne S De Groot, Robert T Chen |
22355779 | Hepatitis C virus antigenic convergence | David S Campo, Zoya Dimitrova, Jonny Yokosawa, Duc Hoang, Nestor O Perez, Sumathi Ramachandran, Yury Khudyakov |
22421792 | Modeling chemical interaction profiles: I. Spectral data-activity relationship and structure-activity relationship models for inhibitors and non-inhibitors of cytochrome P450 CYP3A4 and CYP2D6 isozymes | Brooks McPhail, Yunfeng Tie, Huixiao Hong, Bruce A Pearce, Laura K Schnackenberg, Weigong Ge, Luis G Valerio, James C Fuscoe, Weida Tong, Dan A Buzatu, Jon G Wilkes, Bruce A Fowler, Eugene Demchuk, Richard D Beger |
22634542 | Towards automatic diabetes case detection and ABCS protocol compliance assessment | Ninad K Mishra, Roderick Y Son, James J Arnzen |
23152765 | Sensitive and specific peak detection for SELDI-TOF mass spectrometry using a wavelet/neural-network based approach | Vincent A Emanuele 2nd, Gitika Panicker, Brian M Gurbaxani, Jin-Mann S Lin, Elizabeth R Unger |
23202418 | Differences in variability of hypervariable region 1 of hepatitis C virus (HCV) between acute and chronic stages of HCV infection | I V Astrakhantseva, D S Campo, A Araujo, C-G Teo, Y Khudyakov, S Kamili |
23202423 | Coordinated evolution among hepatitis C virus genomic sites is coupled to host factors and resistance to interferon | James Lara, John E Tavis, Maureen J Donlin, William M Lee, He-Jun Yuan, Brian L Pearlman, Gilberto Vaughan, Joseph C Forbi, Guo-Liang Xia, Yury E Khudyakov |
23206504 | Development and evaluation of a Naïve Bayesian model for coding causation of workers’ compensation claims | S J Bertke, A R Meyers, S J Wurzelbacher, J Bell, M L Lampl, D Robins |
24461165 | Multivariate adaptive regression splines analysis to predict biomarkers of spontaneous preterm birth | Ramkumar Menon, Geeta Bhat, George R Saade, Heidi Spratt |
24466291 | LABEL: fast and accurate lineage assignment with assessment of H5N1 and H9N2 influenza A hemagglutinins | Samuel S Shepard, C Todd Davis 1 , Justin Bahl 2 , Pierre Rivailler 1 , Ian A York 1 , Ruben O Donis 1 |
25081062 | Computational models of liver fibrosis progression for hepatitis C virus chronic infection | James Lara, F López-Labrador, Fernando González-Candelas, Marina Berenguer, Yury E Khudyakov |
25341363 | Estimating contact rates at a mass gathering by using video analysis: a proof-of-concept project | Jeanette J Rainey, Anil Cheriyadat, Richard J Radke, Julie Suzuki Crumly, Daniel B Koch |
25558292 | Individualized Survival and Treatment Response Predictions in Breast Cancer Patients: Involvements of Phospho-EGFR and Phospho-Her2/neu Proteins | Lan Guo, Jame Abraham, Daniel C Flynn, Vincent Castranova, Xianglin Shi, Yong Qian |
25666908 | Using multiple sources of data for surveillance of postoperative venous thromboembolism among surgical patients treated in Department of Veterans Affairs hospitals, 2005-2010 | Richard E Nelson, Scott D Grosse, Norman J Waitzman, Junji Lin, Scott L DuVall, Olga Patterson, James Tsai, Nimia Reyes |
25672399 | Use of random forest to estimate population attributable fractions from a case-control study of Salmonella enterica serotype Enteritidis infections | W Gu, A R Vieira, R M Hoekstra, P M Griffin, D Cole |
26216993 | Novel serologic biomarkers provide accurate estimates of recent Plasmodium falciparum exposure for individuals and communities | Danica A Helb, Kevin K A Tetteh, Philip L Felgner, Jeff Skinner, Alan Hubbard, Emmanuel Arinaitwe, Harriet Mayanja-Kizza, Isaac Ssewanyana, Moses R Kamya, James G Beeson, Jordan Tappero, David L Smith, Peter D Crompton, Philip J Rosenthal, Grant Dorsey, Christopher J Drakeley, Bryan Greenhouse |
26610292 | Presence of an epigenetic signature of prenatal cigarette smoke exposure in childhood | Christine Ladd-Acosta, Chang Shu, Brian K Lee, Nicole Gidaya, Alison Singer, Laura A Schieve, Diana E Schendel, Nicole Jones, Julie L Daniels, Gayle C Windham, Craig J Newschaffer, Lisa A Croen, Andrew P Feinberg, M Daniele Fallin |
26745274 | Comparison of methods for auto-coding causation of injury narratives | S J Bertke, A R Meyers, S J Wurzelbacher, A Measure, M P Lampl, D Robins |
27280867 | A knowledge base for tracking the impact of genomics on population health | Wei Yu, Marta Gwinn, W David Dotson, Ridgely Fisk Green, Mindy Clyne, Anja Wulf, Scott Bowen, Katherine Kolor, Muin J Khoury |
27412252 | Dysbiosis, inflammation, and response to treatment: a longitudinal study of pediatric subjects with newly diagnosed inflammatory bowel disease | Kelly A Shaw, Madeline Bertha, Tatyana Hofmekler, Pankaj Chopra, Tommi Vatanen, Abhiram Srivatsa, Jarod Prince, Archana Kumar, Cary Sauer, Michael E Zwick, Glen A Satten, Aleksandar D Kostic, Jennifer G Mulle, Ramnik J Xavier, Subra Kugathasan |
27585810 | Finishing monkeypox genomes from short reads: assembly analysis and a neural network method | Kun Zhao, Robert M Wohlhueter, Yu Li |
28002438 | Development of a Machine Learning Algorithm for the Surveillance of Autism Spectrum Disorder | Matthew J Maenner, Marshalyn Yeargin-Allsopp, Kim Van Naarden Braun, Deborah L Christensen, Laura A Schieve |
28210420 | Cross-Disciplinary Consultancy to Enhance Predictions of Asthma Exacerbation Risk in Boston | Margaret Reid, Julia Gunn, Snehal Shah, Michael Donovan, Rosalind Eggo, Steven Babin, Ivanka Stajner, Eric Rogers, Katherine B Ensor, Loren Raun, Jonathan I Levy, Ian Painter, Wanda Phipatanakul, Fuyuen Yip, Anjali Nath, Laura C Streichert, Catherine Tong, Howard Burkom |
28395357 | Development of the SaFETy Score: A Clinical Screening Tool for Predicting Future Firearm Violence Risk | Jason E Goldstick, Patrick M Carter, Maureen A Walton, Linda L Dahlberg, Steven A Sumner, Marc A Zimmerman, Rebecca M Cunningham |
28542223 | Measuring changes in transmission of neglected tropical diseases, malaria, and enteric pathogens from quantitative antibody levels | Benjamin F Arnold, Mark J van der Laan, Alan E Hubbard, Cathy Steel, Joseph Kubofcik, Katy L Hamlin, Delynn M Moss, Thomas B Nutman, Jeffrey W Priest, Patrick J Lammie |
28810827 | Validation of β-lactam minimum inhibitory concentration predictions for pneumococcal isolates with newly encountered penicillin binding protein (PBP) sequences | Yuan Li, Benjamin J Metcalf, Sopio Chochua, Zhongya Li, Robert E Gertz Jr, Hollis Walker, Paulina A Hawkins, Theresa Tran, Lesley McGee, Bernard W Beall, Active Bacterial Core surveillance team |
28814545 | Metabolic differentiation of early Lyme disease from southern tick-associated rash illness (STARI) | Claudia R Molins, Laura V Ashton, Gary P Wormser, Barbara G Andre, Ann M Hess, Mark J Delorey, Mark A Pilgard, Barbara J Johnson, Kristofor Webb, M Nurul Islam, Adoracion Pegalajar-Jurado, Irida Molla, Mollie W Jewett, John T Belisle |
28934917 | Sparse Supervised Classification Methods Predict and Characterize Nanomaterial Exposures: Independent Markers of MWCNT Exposures | Naveena Yanamala, Marlene S Orandle, Vamsi K Kodali, Lindsey Bishop, Patti C Zeidler-Erdely, Jenny R Roberts, Vincent Castranova, Aaron Erdely |
28953071 | Applying Machine Learning to Workers’ Compensation Data to Identify Industry-Specific Ergonomic and Safety Prevention Priorities: Ohio, 2001 to 2011 | Alysha R Meyers, Ibraheem S Al-Tarawneh, Steven J Wurzelbacher, P Timothy Bushnell, Michael P Lampl, Jennifer L Bell, Stephen J Bertke, David C Robins, Chih-Yu Tseng, Chia Wei, Jill A Raudabaugh, Teresa M Schnorr |
29028799 | Modeling the environmental suitability of anthrax in Ghana and estimating populations at risk: Implications for vaccination and control | Ian T Kracalik, Ernest Kenu, Evans Nsoh Ayamdooh, Emmanuel Allegye-Cudjoe, Paul Nokuma Polkuu, Joseph Asamoah Frimpong, Kofi Mensah Nyarko, William A Bower, Rita Traxler, Jason K Blackburn |
29087984 | Improved Identification of Venous Thromboembolism From Electronic Medical Records Using a Novel Information Extraction Software Platform | Raymund B Dantes, Shuai Zheng, James J Lu, Michele G Beckman, Asha Krishnaswamy, Lisa C Richardson, Sheri Chernetsky-Tejedor, Fusheng Wang |
29216422 | Distinguishing Petroleum (Crude Oil and Fuel) From Smoke Exposure within Populations Based on the Relative Blood Levels of Benzene, Toluene, Ethylbenzene, and Xylenes (BTEX), Styrene and 2,5-Dimethylfuran by Pattern Recognition Using Artificial Neural Networks | D M Chambers, C M Reese, L G Thornburg, E Sanchez, J P Rafson, B C Blount, J R E Ruhl 3rd, V R De Jesús |
29244000 | Identification of recent cases of hepatitis C virus infection using physical-chemical properties of hypervariable region 1 and a radial basis function neural network classifier | James Lara, Mahder Teka, Yury Khudyakov |
29453090 | Evaluating effects of prenatal exposure to phthalate mixtures on birth weight: A comparison of three statistical approaches | Yu-Han Chiu, Andrea Bellavia, Tamarra James-Todd, Katharine F Correia, Linda Valeri, Carmen Messerlian, Jennifer B Ford, Lidia Mínguez-Alarcón, Antonia M Calafat, Russ Hauser, Paige L Williams, EARTH Study Team |
29545462 | Impact of Intensive Lifestyle Intervention on Disability-Free Life Expectancy: The Look AHEAD Study | Edward W Gregg, Ji Lin, Barbara Bardenheier, Haiying Chen, W Jack Rejeski, Xiaohui Zhuo, Andrea L Hergenroeder, Stephen B Kritchevsky, Anne L Peters, Lynne E Wagenknecht, Edward H Ip, Mark A Espeland, Look AHEAD Study Group |
29563765 | Experimental study on foam coverage on simulated longwall roof | W R Reed, Y Zheng, S Klima, M R Shahan, T W Beck |
29613851 | Solution to Detect, Classify, and Report Illicit Online Marketing and Sales of Controlled Substances via Twitter: Using Machine Learning and Web Forensics to Combat Digital Opioid Access | Tim Mackey , Janani Kalyanam, Josh Klugman, Ella Kuzmenko, Rashmi Gupta |
29792563 | Ability of crime, demographic and business data to forecast areas of increased violence | Daniel A Bowen, Laura M Mercer Kollar, Daniel T Wu, David A Fraser, Charles E Flood, Jasmine C Moore, Elizabeth W Mays, Steven A Sumner |
29860098 | Intelligent Network DisRuption Analysis (INDRA): A targeted strategy for efficient interruption of hepatitis C transmissions | David S Campo, Yury Khudyakov |
29950689 | A taxonomic signature of obesity in a large study of American adults | Brandilyn A Peters, Jean A Shapiro, Timothy R Church, George Miller, Chau Trinh-Shevrin, Elizabeth Yuen, Charles Friedlander, Richard B Hayes, Jiyoung Ahn |
30197419 | HLBS-PopOmics: an online knowledge base to accelerate dissemination and implementation of research advances in population genomics to reduce the burden of heart, lung, blood, and sleep disorders | George A Mensah, Wei Yu, Whitney L Barfield, Mindy Clyne, Michael M Engelgau, Muin J Khoury |
30309799 | Effectiveness of strategies to improve health-care provider practices in low-income and middle-income countries: a systematic review | Alexander K Rowe, Samantha Y Rowe, David H Peters, Kathleen A Holloway, John Chalker, Dennis Ross-Degnan |
30343674 | Automated quality control for a molecular surveillance system | Seth Sims, Atkinson G Longmire, David S Campo, Sumathi Ramachandran, Magdalena Medrzycki, Lilia Ganova-Raeva, Yulin Lin, Amanda Sue, Hong Thai, Alexander Zelikovsky, Yury Khudyakov |
30381005 | Causal inference with multiple concurrent medications: A comparison of methods and an application in multidrug-resistant tuberculosis | Arman Alam Siddique, Mireille E Schnitzer, Asma Bahamyirou, Guanbo Wang, Timothy H Holtz, Giovanni B Migliori, Giovanni Sotgiu, Neel R Gandhi, Mario H Vargas, Dick Menzies, Andrea Benedetti |
30561314 | Zoonotic Source Attribution of Salmonella enterica Serotype Typhimurium Using Genomic Surveillance Data, United States | Shaokang Zhang, Shaoting Li, Weidong Gu, Henk den Bakker, Dave Boxrud, Angie Taylor, Chandler Roe, Elizabeth Driebe, David M Engelthaler, Marc Allard, Eric Brown, Patrick McDermott, Shaohua Zhao, Beau B Bruce, Eija Trees, Patricia I Fields, Xiangyu Deng |
30586440 | Genotypic differences between strains of the opportunistic pathogen Corynebacterium bovis isolated from humans, cows, and rodents | Christopher Cheleuitte-Nieves, Christopher A Gulvik, John R McQuiston, Ben W Humrighouse, Melissa E Bell, Aaron Villarma, Vincent A Fischetti, Lars F Westblade, Neil S Lipman |
30625130 | Using machine learning and an ensemble of methods to predict kidney transplant survival | Ethan Mark, David Goldsman, Brian Gurbaxani, Pinar Keskinocak, Joel Sokol |
30635558 | Improved state-level influenza nowcasting in the United States leveraging Internet-based data and network approaches | Fred S Lu, Mohammad W Hattab, Cesar Leonardo Clemente, Matthew Biggerstaff, Mauricio Santillana |
30687797 | Natural language generation for electronic health records | Scott H Lee |
30753477 | Using deep learning to identify translational research in genomic medicine beyond bench to bedside | Yi-Yu Hsu, Mindy Clyne, Chih-Hsuan Wei, Muin J Khoury, Zhiyong Lu |
30926471 | Chief complaint classification with recurrent neural networks | Scott H Lee, Drew Levin, Patrick D Finley, Charles M Heilig |
31111463 | Automated detection of sudden unexpected death in epilepsy risk factors in electronic medical records using natural language processing | Kristen Barbour, Dale C Hesdorffer, Niu Tian, Elissa G Yozawitz, Patricia E McGoldrick, Steven Wolf, Tiffani L McDonough, Aaron Nelson, Tobias Loddenkemper, Natasha Basma, Stephen B Johnson, Zachary M Grinspan |
31128829 | The use of natural language processing to identify Tdap-related local reactions at five health care systems in the Vaccine Safety Datalink | Chengyi Zheng, Wei Yu, Fagen Xie, Wansu Chen, Cheryl Mercado, Lina S Sy, Lei Qian, Sungching Glenn, Gina Lee, Hung Fu Tseng, Jonathan Duffy, Lisa A Jackson, Matthew F Daley, Brad Crane, Huong Q McLean, Steven J Jacobsen |
31167647 | Entropy of mitochondrial DNA circulating in blood is associated with hepatocellular carcinoma | David S Campo, Vishal Nayak, Ganesh Srinivasamoorthy, Yury Khudyakov |
31280638 | Grouping of carbonaceous nanomaterials based on association of patterns of inflammatory markers in BAL fluid with adverse outcomes in lungs | Naveena Yanamala, Ishika C Desai, William Miller, Vamsi K Kodali, Girija Syamlal, Jenny R Roberts, Aaron D Erdely |
31314253 | Improving Patient Cohort Identification Using Natural Language Processing | Raymond Francis Sarmiento, Franck Dernoncourt |
31553774 | A comparison of machine learning algorithms for the surveillance of autism spectrum disorder | Scott H Lee, Matthew J Maenner, Charles M Heilig |
31608599 | FluChip-8G Insight: HA and NA subtyping of potentially pandemic influenza A viruses in a single assay | Evan Toth, Erica D Dawson, Amber W Taylor, Robert S Stoughton, Rebecca H Blair, James E Johnson Jr, Amelia Slinskey, Ryan Fessler, Catherine B Smith, Sarah Talbot, Kathy Rowlen |
31797475 | The use of natural language processing to identify vaccine-related anaphylaxis at five health care systems in the Vaccine Safety Datalink | Wei Yu 1 , Chengyi Zheng 1 , Fagen Xie 1 , Wansu Chen 1 , Cheryl Mercado 1 , Lina S Sy 1 , Lei Qian 1 , Sungching Glenn, Hung F Tseng, Gina Lee, Jonathan Duffy, Michael M McNeil, Matthew F Daley, Brad Crane, Huong Q McLean, Lisa A Jackson, Steven J Jacobsen |
31899451 | The Detection of Opioid Misuse and Heroin Use From Paramedic Response Documentation: Machine Learning for Improved Surveillance | José Tomás Prieto, Kenneth Scott, Dean McEwen, Laura J Podewils, Alia Al-Tayyib, James Robinson, David Edwards, Seth Foldy, Judith C Shlay, Arthur J Davidson |
32015431 | TREXMO plus: an advanced self-learning model for occupational exposure assessment | Nenad Savic, Eun Gyung Lee, Bojan Gasic, David Vernez |
32049631 | Characterizing the weight-glycemia phenotypes of type 1 diabetes in youth and young adulthood | Anna R Kahkoska, Crystal T Nguyen, Xiaotong Jiang, Linda A Adair, Shivani Agarwal, Allison E Aiello, Kyle S Burger, John B Buse, Dana Dabelea, Lawrence M Dolan, Giuseppina Imperatore, Jean Marie Lawrence, Santica Marcovina, Catherine Pihoker, Beth A Reboussin, Katherine A Sauder, Michael R Kosorok, Elizabeth J Mayer-Davis |
32372243 | Using Supervised Learning Methods to Develop a List of Prescription Medications of Greatest Concern during Pregnancy | Elizabeth C Ailes, John Zimmerman, Jennifer N Lind, Fanghui Fan, Kun Shi, Jennita Reefhuis, Cheryl S Broussard, Meghan T Frey, Janet D Cragan, Emily E Petersen, Kara D Polen, Margaret A Honein, Suzanne M Gilboa |
32387013 | Intent to obtain pediatric influenza vaccine among mothers in four middle income countries | Abram L Wagner, Aubree Gordon, Veronica L Tallo, Artan Simaku, Rachael M Porter, Laura J Edwards, Enkeleda Duka, Ilham Abu-Khader, Lionel Gresh, Cristina Sciuto, Eduardo Azziz-Baumgartner, Silvia Bino, Felix Sanchez, Guillermina Kuan, Joanne N de Jesus, Eric A F Simões, Danielle R Hunt, Ali K Arbaji, Mark G Thompson |
32478331 | Machine learning can accelerate discovery and application of cyber-molecular cancer diagnostics | David S Campo, Yury Khudyakov |
32810028 | Can Machine Learning Help Identify Patients at Risk for Recurrent Sexually Transmitted Infections? | Heather R Elder, Susan Gruber, Sarah J Willis, Noelle Cocoros, Myfanwy Callahan, Elaine W Flagg, Michael Klompas, Katherine K Hsu |
32815300 | Exploratory analysis of machine learning approaches for surveillance of Zika-associated birth defects | Richard Lusk, John Zimmerman, Kelley VanMaldeghem, Suzanna Kim, Nicole M Roth, James Lavinder, Anna Fulton, Meghan Raycraft, Sascha R Ellington, Romeo R Galang |
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