Full Text Journal Articles by
Author Rayid Ghani

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Validation of a Machine Learning Model to Predict Childhood Lead Poisoning.

Eric Potash, Rayid Ghani, Joe Walsh, Emile Jorgensen, Cortland Lohff, Nik Prachand, Raed Mansour,

<h4>Importance</h4>Childhood lead poisoning causes irreversible neurobehavioral deficits, but current practice is secondary prevention.<h4>Objective</h4>To validate a machine learning (random forest) prediction model of elevated blood lead levels (EBLLs) by comparison with a parsimonious logistic regression.<h4>Design, setting, and participants</h4>This prognostic study for temporal validation of multivariable prediction models used data from the ... Read more >>

JAMA Netw Open (JAMA network open)
[2020, 3(9):e2012734]

Cited: 0 times

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Predictive Analytics for Retention in Care in an Urban HIV Clinic.

Arthi Ramachandran, Avishek Kumar, Hannes Koenig, Adolfo De Unanue, Christina Sung, Joe Walsh, John Schneider, Rayid Ghani, Jessica P Ridgway,

Consistent medical care among people living with HIV is essential for both individual and public health. HIV-positive individuals who are 'retained in care' are more likely to be prescribed antiretroviral medication and achieve HIV viral suppression, effectively eliminating the risk of transmitting HIV to others. However, in the United States, ... Read more >>

Sci Rep (Scientific reports)
[2020, 10(1):6421]

Cited: 3 times

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Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness.

Sebastian Vollmer, Bilal A Mateen, Gergo Bohner, Franz J Király, Rayid Ghani, Pall Jonsson, Sarah Cumbers, Adrian Jonas, Katherine S L McAllister, Puja Myles, David Granger, Mark Birse, Richard Branson, Karel G M Moons, Gary S Collins, John P A Ioannidis, Chris Holmes, Harry Hemingway,

BMJ (BMJ (Clinical research ed.))
[2020, 368:l6927]

Cited: 29 times

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An Experience-Centered Approach to Training Effective Data Scientists.

Kit T Rodolfa, Adolfo De Unanue, Matt Gee, Rayid Ghani,

Like medicine, psychology, or education, data science is fundamentally an applied discipline, with most students who receive advanced degrees in the field going on to work on practical problems. Unlike these disciplines, however, data science education remains heavily focused on theory and methods, and practical coursework typically revolves around cleaned ... Read more >>

Big Data (Big data)
[2019, 7(4):249-261]

Cited: 0 times

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Using Ensemble Machine Learning Methods for Predicting Risk of Readmission for Heart Failure.

Satish M Mahajan, Rayid Ghani,

Recently, researchers have been applying many new machine learning techniques for predicting the risk of readmission for heart failure. Combining such techniques through ensemble schemes holds a promise to further harness predictive performance of the resulting models. To that end, we examined two ensemble schemes and applied them to a ... Read more >>

Stud Health Technol Inform (Studies in health technology and informatics)
[2019, 264:243-247]

Cited: 4 times

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Combining Structured and Unstructured Data for Predicting Risk of Readmission for Heart Failure Patients.

Satish M Mahajan, Rayid Ghani,

Researchers have studied many models for predicting the risk of readmission for heart failure over the last decade. Most models have used a parametric statistical approach while a few have ventured into using machine learning methods such as statistical natural language processing. We created three predictive models by combining these ... Read more >>

Stud Health Technol Inform (Studies in health technology and informatics)
[2019, 264:238-242]

Cited: 2 times

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Machine Learning for Social Services: A Study of Prenatal Case Management in Illinois.

Ian Pan, Laura B Nolan, Rashida R Brown, Romana Khan, Paul van der Boor, Daniel G Harris, Rayid Ghani,

<h4>Objectives</h4>To evaluate the positive predictive value of machine learning algorithms for early assessment of adverse birth risk among pregnant women as a means of improving the allocation of social services.<h4>Methods</h4>We used administrative data for 6457 women collected by the Illinois Department of Human Services from July 2014 to May 2015 ... Read more >>

Am J Public Health (American journal of public health)
[2017, 107(6):938-944]

Cited: 5 times

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Big Data for Social Good.

Charlie Catlett, Rayid Ghani,

Big Data (Big data)
[2015, 3(1):1-2]

Cited: 0 times

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