lunes, 28 de septiembre de 2020

Artificial Intelligence, Public Trust, and Public Health | | Blogs | CDC

Artificial Intelligence, Public Trust, and Public Health | | Blogs | CDC

Artificial Intelligence, Public Trust, and Public Health

Posted on  by Carlos Siordia PhD, Office of Science Fellow and Muin J. Khoury MD, PhD, Director, Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, Georgia

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As 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 IDTitleAuthors
14700412Electronic interpretation of chest radiograph reports to detect central venous cathetersWilliam E Trick, Wendy W Chapman, Mary F Wisniewski, Brian J Peterson, Steven L Solomon, Robert A Weinstein
15217815Standardization and denoising algorithms for mass spectra to classify whole-organism bacterial specimensGlen A Satten, Somnath Datta, Hercules Moura, Adrian R Woolfitt, Maria da G Carvalho, George M Carlone, Barun K De, Antonis Pavlopoulos, John R Barr
16606998Predicting density of Ixodes pacificus nymphs in dense woodlands in Mendocino County, California, based on geographic information systems and remote sensing versus field-derived dataRebecca J Eisen, Lars Eisen, Robert S Lane
16610958Allostatic load is associated with symptoms in chronic fatigue syndrome patientsBenjamin N Goertzel, Cassio Pennachin, Lucio de Souza Coelho, Elizabeth M Maloney, James F Jones, Brian Gurbaxani
16899605Predicting cancer drug response by proteomic profilingYan Ma, Zhenyu Ding, Yong Qian, Xianglin Shi, Vince Castranova, E James Harner, Lan Guo
17109381Discrimination of intact mycobacteria at the strain level: a combined MALDI-TOF MS and biostatistical analysisJustin M Hettick, Michael L Kashon, James E Slaven, Yan Ma, Janet P Simpson, Paul D Siegel, Gerald N Mazurek, David N Weissman
17238741Concept negation in free text components of vaccine safety reportsHerman Tolentino, Michael Matters, Wikke Walop, Barbara Law, Wesley Tong, Fang Liu, Paul Fontelo, Katrin Kohl, Daniel Payne
17295907A UMLS-based spell checker for natural language processing in vaccine safetyHerman D Tolentino, Michael D Matters, Wikke Walop, Barbara Law, Wesley Tong, Fang Liu, Paul Fontelo, Katrin Kohl, Daniel C Payne
17654333A new descriptor selection scheme for SVM in unbalanced class problem: a case study using skin sensitisation datasetS Li, A Fedorowicz, M E Andrew
17996092An open source infrastructure for managing knowledge and finding potential collaborators in a domain-specific subset of PubMed, with an example from human genome epidemiologyWei Yu, Ajay Yesupriya, Anja Wulf, Junfeng Qu, Muin J Khoury, Marta Gwinn
18430222GAPscreener: an automatic tool for screening human genetic association literature in PubMed using the support vector machine techniqueWei Yu, Melinda Clyne, Siobhan M Dolan, Ajay Yesupriya, Anja Wulf, Tiebin Liu, Muin J Khoury, Marta Gwinn
18537829MALDI-TOF mass spectrometry as a tool for differentiation of invasive and noninvasive Streptococcus pyogenes isolatesHercules Moura, Adrian R Woolfitt, Maria G Carvalho, Antonis Pavlopoulos, Lucia M Teixeira, Glen A Satten, John R Barr
18628290Artificial neural network for prediction of antigenic activity for a major conformational epitope in the hepatitis C virus NS3 proteinJames Lara, Robert M Wohlhueter, Zoya Dimitrova, Yury E Khudyakov
18708515Differentiation of Streptococcus pneumoniae conjunctivitis outbreak isolates by matrix-assisted laser desorption ionization-time of flight mass spectrometryYulanda 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
19390102A rule-based approach for identifying obesity and its comorbidities in medical discharge summariesNinad K Mishra, David M Cummo, James J Arnzen, Jason Bonander
19864262A rule-based approach for identifying obesity and its comorbidities in medical discharge summariesNinad K Mishra, David M Cummo, James J Arnzen, Jason Bonander
20307319Application of support vector machine modeling for prediction of common diseases: the case of diabetes and pre-diabetesWei Yu, Tiebin Liu, Rodolfo Valdez, Marta Gwinn, Muin J Khoury
20942945Quadratic variance models for adaptively preprocessing SELDI-TOF mass spectrometry dataVincent A Emanuele 2nd, Brian M Gurbaxani
21772787Emerging vaccine informaticsYongqun He, Rino Rappuoli, Anne S De Groot, Robert T Chen
22355779Hepatitis C virus antigenic convergenceDavid S Campo, Zoya Dimitrova, Jonny Yokosawa, Duc Hoang, Nestor O Perez, Sumathi Ramachandran, Yury Khudyakov
22421792Modeling chemical interaction profiles: I. Spectral data-activity relationship and structure-activity relationship models for inhibitors and non-inhibitors of cytochrome P450 CYP3A4 and CYP2D6 isozymesBrooks 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
22634542Towards automatic diabetes case detection and ABCS protocol compliance assessmentNinad K Mishra, Roderick Y Son, James J Arnzen
23152765Sensitive and specific peak detection for SELDI-TOF mass spectrometry using a wavelet/neural-network based approachVincent A Emanuele 2nd, Gitika Panicker, Brian M Gurbaxani, Jin-Mann S Lin, Elizabeth R Unger
23202418Differences in variability of hypervariable region 1 of hepatitis C virus (HCV) between acute and chronic stages of HCV infectionI V Astrakhantseva, D S Campo, A Araujo, C-G Teo, Y Khudyakov, S Kamili
23202423Coordinated evolution among hepatitis C virus genomic sites is coupled to host factors and resistance to interferonJames 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
23206504Development and evaluation of a Naïve Bayesian model for coding causation of workers’ compensation claimsS J Bertke, A R Meyers, S J Wurzelbacher, J Bell, M L Lampl, D Robins
24461165Multivariate adaptive regression splines analysis to predict biomarkers of spontaneous preterm birthRamkumar Menon, Geeta Bhat, George R Saade, Heidi Spratt
24466291LABEL: fast and accurate lineage assignment with assessment of H5N1 and H9N2 influenza A hemagglutininsSamuel S Shepard, C Todd Davis 1 , Justin Bahl 2 , Pierre Rivailler 1 , Ian A York 1 , Ruben O Donis 1
25081062Computational models of liver fibrosis progression for hepatitis C virus chronic infectionJames Lara, F López-Labrador, Fernando González-Candelas, Marina Berenguer, Yury E Khudyakov
25341363Estimating contact rates at a mass gathering by using video analysis: a proof-of-concept projectJeanette J Rainey, Anil Cheriyadat, Richard J Radke, Julie Suzuki Crumly, Daniel B Koch
25558292Individualized Survival and Treatment Response Predictions in Breast Cancer Patients: Involvements of Phospho-EGFR and Phospho-Her2/neu ProteinsLan Guo, Jame Abraham, Daniel C Flynn, Vincent Castranova, Xianglin Shi, Yong Qian
25666908Using multiple sources of data for surveillance of postoperative venous thromboembolism among surgical patients treated in Department of Veterans Affairs hospitals, 2005-2010Richard E Nelson, Scott D Grosse, Norman J Waitzman, Junji Lin, Scott L DuVall, Olga Patterson, James Tsai, Nimia Reyes
25672399Use of random forest to estimate population attributable fractions from a case-control study of Salmonella enterica serotype Enteritidis infectionsW Gu, A R Vieira, R M Hoekstra, P M Griffin, D Cole
26216993Novel serologic biomarkers provide accurate estimates of recent Plasmodium falciparum exposure for individuals and communitiesDanica 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
26610292Presence of an epigenetic signature of prenatal cigarette smoke exposure in childhoodChristine 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
26745274Comparison of methods for auto-coding causation of injury narrativesS J Bertke, A R Meyers, S J Wurzelbacher, A Measure, M P Lampl, D Robins
27280867A knowledge base for tracking the impact of genomics on population healthWei Yu, Marta Gwinn, W David Dotson, Ridgely Fisk Green, Mindy Clyne, Anja Wulf, Scott Bowen, Katherine Kolor, Muin J Khoury
27412252Dysbiosis, inflammation, and response to treatment: a longitudinal study of pediatric subjects with newly diagnosed inflammatory bowel diseaseKelly 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
27585810Finishing monkeypox genomes from short reads: assembly analysis and a neural network methodKun Zhao, Robert M Wohlhueter, Yu Li
28002438Development of a Machine Learning Algorithm for the Surveillance of Autism Spectrum DisorderMatthew J Maenner, Marshalyn Yeargin-Allsopp, Kim Van Naarden Braun, Deborah L Christensen, Laura A Schieve
28210420Cross-Disciplinary Consultancy to Enhance Predictions of Asthma Exacerbation Risk in BostonMargaret 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
28395357Development of the SaFETy Score: A Clinical Screening Tool for Predicting Future Firearm Violence RiskJason E Goldstick, Patrick M Carter, Maureen A Walton, Linda L Dahlberg, Steven A Sumner, Marc A Zimmerman, Rebecca M Cunningham
28542223Measuring changes in transmission of neglected tropical diseases, malaria, and enteric pathogens from quantitative antibody levelsBenjamin 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
28810827Validation of β-lactam minimum inhibitory concentration predictions for pneumococcal isolates with newly encountered penicillin binding protein (PBP) sequencesYuan 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
28814545Metabolic 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
28934917Sparse Supervised Classification Methods Predict and Characterize Nanomaterial Exposures: Independent Markers of MWCNT ExposuresNaveena Yanamala, Marlene S Orandle, Vamsi K Kodali, Lindsey Bishop, Patti C Zeidler-Erdely, Jenny R Roberts, Vincent Castranova, Aaron Erdely
28953071Applying Machine Learning to Workers’ Compensation Data to Identify Industry-Specific Ergonomic and Safety Prevention Priorities: Ohio, 2001 to 2011Alysha 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
29028799Modeling the environmental suitability of anthrax in Ghana and estimating populations at risk: Implications for vaccination and controlIan 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
29087984Improved Identification of Venous Thromboembolism From Electronic Medical Records Using a Novel Information Extraction Software PlatformRaymund B Dantes, Shuai Zheng, James J Lu, Michele G Beckman, Asha Krishnaswamy, Lisa C Richardson, Sheri Chernetsky-Tejedor, Fusheng Wang
29216422Distinguishing 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 NetworksD 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
29244000Identification of recent cases of hepatitis C virus infection using physical-chemical properties of hypervariable region 1 and a radial basis function neural network classifierJames Lara, Mahder Teka, Yury Khudyakov
29453090Evaluating effects of prenatal exposure to phthalate mixtures on birth weight: A comparison of three statistical approachesYu-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
29545462Impact of Intensive Lifestyle Intervention on Disability-Free Life Expectancy: The Look AHEAD StudyEdward 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
29563765Experimental study on foam coverage on simulated longwall roofW R Reed, Y Zheng, S Klima, M R Shahan, T W Beck
29613851Solution 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 AccessTim Mackey , Janani Kalyanam, Josh Klugman, Ella Kuzmenko, Rashmi Gupta
29792563Ability of crime, demographic and business data to forecast areas of increased violenceDaniel A Bowen, Laura M Mercer Kollar, Daniel T Wu, David A Fraser, Charles E Flood, Jasmine C Moore, Elizabeth W Mays, Steven A Sumner
29860098Intelligent Network DisRuption Analysis (INDRA): A targeted strategy for efficient interruption of hepatitis C transmissionsDavid S Campo, Yury Khudyakov
29950689A taxonomic signature of obesity in a large study of American adultsBrandilyn A Peters, Jean A Shapiro, Timothy R Church, George Miller, Chau Trinh-Shevrin, Elizabeth Yuen, Charles Friedlander, Richard B Hayes, Jiyoung Ahn
30197419HLBS-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 disordersGeorge A Mensah, Wei Yu, Whitney L Barfield, Mindy Clyne, Michael M Engelgau, Muin J Khoury
30309799Effectiveness of strategies to improve health-care provider practices in low-income and middle-income countries: a systematic reviewAlexander K Rowe, Samantha Y Rowe, David H Peters, Kathleen A Holloway, John Chalker, Dennis Ross-Degnan
30343674Automated quality control for a molecular surveillance systemSeth Sims, Atkinson G Longmire, David S Campo, Sumathi Ramachandran, Magdalena Medrzycki, Lilia Ganova-Raeva, Yulin Lin, Amanda Sue, Hong Thai, Alexander Zelikovsky, Yury Khudyakov
30381005Causal inference with multiple concurrent medications: A comparison of methods and an application in multidrug-resistant tuberculosisArman 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
30561314Zoonotic Source Attribution of Salmonella enterica Serotype Typhimurium Using Genomic Surveillance Data, United StatesShaokang 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
30586440Genotypic differences between strains of the opportunistic pathogen Corynebacterium bovis isolated from humans, cows, and rodentsChristopher 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
30625130Using machine learning and an ensemble of methods to predict kidney transplant survivalEthan Mark, David Goldsman, Brian Gurbaxani, Pinar Keskinocak, Joel Sokol
30635558Improved state-level influenza nowcasting in the United States leveraging Internet-based data and network approachesFred S Lu, Mohammad W Hattab, Cesar Leonardo Clemente, Matthew Biggerstaff, Mauricio Santillana
30687797Natural language generation for electronic health recordsScott H Lee
30753477Using deep learning to identify translational research in genomic medicine beyond bench to bedsideYi-Yu Hsu, Mindy Clyne, Chih-Hsuan Wei, Muin J Khoury, Zhiyong Lu
30926471Chief complaint classification with recurrent neural networksScott H Lee, Drew Levin, Patrick D Finley, Charles M Heilig
31111463Automated detection of sudden unexpected death in epilepsy risk factors in electronic medical records using natural language processingKristen 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
31128829The use of natural language processing to identify Tdap-related local reactions at five health care systems in the Vaccine Safety DatalinkChengyi 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
31167647Entropy of mitochondrial DNA circulating in blood is associated with hepatocellular carcinomaDavid S Campo, Vishal Nayak, Ganesh Srinivasamoorthy, Yury Khudyakov
31280638Grouping of carbonaceous nanomaterials based on association of patterns of inflammatory markers in BAL fluid with adverse outcomes in lungsNaveena Yanamala, Ishika C Desai, William Miller, Vamsi K Kodali, Girija Syamlal, Jenny R Roberts, Aaron D Erdely
31314253Improving Patient Cohort Identification Using Natural Language ProcessingRaymond Francis Sarmiento, Franck Dernoncourt
31553774A comparison of machine learning algorithms for the surveillance of autism spectrum disorderScott H Lee, Matthew J Maenner, Charles M Heilig
31608599FluChip-8G Insight: HA and NA subtyping of potentially pandemic influenza A viruses in a single assayEvan 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
31797475The use of natural language processing to identify vaccine-related anaphylaxis at five health care systems in the Vaccine Safety DatalinkWei 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
31899451The Detection of Opioid Misuse and Heroin Use From Paramedic Response Documentation: Machine Learning for Improved SurveillanceJosé Tomás Prieto, Kenneth Scott, Dean McEwen, Laura J Podewils, Alia Al-Tayyib, James Robinson, David Edwards, Seth Foldy, Judith C Shlay, Arthur J Davidson
32015431TREXMO plus: an advanced self-learning model for occupational exposure assessmentNenad Savic, Eun Gyung Lee, Bojan Gasic, David Vernez
32049631Characterizing the weight-glycemia phenotypes of type 1 diabetes in youth and young adulthoodAnna 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
32372243Using Supervised Learning Methods to Develop a List of Prescription Medications of Greatest Concern during PregnancyElizabeth 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
32387013Intent to obtain pediatric influenza vaccine among mothers in four middle income countriesAbram 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
32478331Machine learning can accelerate discovery and application of cyber-molecular cancer diagnosticsDavid S Campo, Yury Khudyakov
32810028Can 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
32815300Exploratory analysis of machine learning approaches for surveillance of Zika-associated birth defectsRichard Lusk, John Zimmerman, Kelley VanMaldeghem, Suzanna Kim, Nicole M Roth, James Lavinder, Anna Fulton, Meghan Raycraft, Sascha R Ellington, Romeo R Galang


Posted on  by Carlos Siordia PhD, Office of Science Fellow and Muin J. Khoury MD, PhD, Director, Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, Georgia

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