AIMC Topic: New York City

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Soft detection of 5-day BOD with sparse matrix in city harbor water using deep learning techniques.

Water research Dec 4, 2019
To better control and manage harbor water quality is an important mission for coastal cities such as New York City (NYC). To achieve this, managers and governors need keep track of key quality indicators, such as temperature, pH, and dissolved oxygen...
Humans Machine Learning Deep Learning Water Cities New York City
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A spatiotemporal deep learning approach for citywide short-term crash risk prediction with multi-source data.

Accident; analysis and prevention Nov 1, 2018
The primary objective of this study is to investigate how the deep learning approach contributes to citywide short-term crash risk prediction by leveraging multi-source datasets. This study uses data collected from Manhattan in New York City to illus...
Humans Risk Assessment New York City Deep Learning Logistic Models Accidents, Traffic Automobiles Weather Spatial Analysis Built Environment
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Learning zero-cost portfolio selection with pattern matching.

PloS one Sep 25, 2018
We replicate and extend the adversarial expert based learning approach of Györfi et al to the situation of zero-cost portfolio selection implemented with a quadratic approximation derived from the mutual fund separation theorems. The algorithm is app...
Machine Learning Models, Economic New York City Algorithms Cluster Analysis South Africa
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Methodological variations in lagged regression for detecting physiologic drug effects in EHR data.

Journal of biomedical informatics Aug 30, 2018
We studied how lagged linear regression can be used to detect the physiologic effects of drugs from data in the electronic health record (EHR). We systematically examined the effect of methodological variations ((i) time series construction, (ii) tem...
Time Factors ROC Curve Regression Analysis Area Under Curve Databases, Factual Electronic Health Records Reproducibility of Results New York City Drug Therapy Pharmaceutical Preparations Data Collection Academic Medical Centers Linear Models Humans Machine Learning
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Towards better prediction of Mycobacterium tuberculosis lineages from MIRU-VNTR data.

Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases Jun 28, 2018
The determination of lineages from strain-based molecular genotyping information is an important problem in tuberculosis. Mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) typing is a commonly used molecular genotyp...
Molecular Epidemiology Databases, Nucleic Acid New York City Interspersed Repetitive Sequences Minisatellite Repeats Computational Biology Tuberculosis Genetic Variation Mycobacterium tuberculosis Humans Machine Learning Phylogeny
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Radiomic features for prostate cancer detection on MRI differ between the transition and peripheral zones: Preliminary findings from a multi-institutional study.

Journal of magnetic resonance imaging : JMRI Dec 19, 2016
PURPOSE: To evaluate in a multi-institutional study whether radiomic features useful for prostate cancer (PCa) detection from 3 Tesla (T) multi-parametric MRI (mpMRI) in the transition zone (TZ) differ from those in the peripheral zone (PZ).
Pilot Projects Humans Magnetic Resonance Imaging Machine Learning Australia Image Interpretation, Computer-Assisted Sensitivity and Specificity Image Enhancement Reproducibility of Results Prostatic Neoplasms Observer Variation Male Aged Finland Internationality Middle Aged Adult New York City Pattern Recognition, Automated
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Food Access in New York City During the COVID-19 Pandemic: Social Media Monitoring Study.

JMIR formative research May 9, 2025
BACKGROUND: The COVID-19 pandemic exacerbated issues of poverty and food insecurity in New York City, and many residents experienced difficulty accessing available resources to help them get food on the table. Social media presents an opportunity to ...
SARS-CoV-2 New York City Humans Social Media Food Insecurity Pandemics Poverty COVID-19 Food Supply
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Application of Natural Language Processing to Learn Insights on the Clinician's Lived Experience of Electronic Health Records.

Studies in health technology and informatics Jan 14, 2022
We interviewed six clinicians to learn about their lived experience using electronic health records (EHR, Allscripts users) using a semi-structured interview guide in an academic medical center in New York City from October to November 2016. Each par...
Electronic Health Records Natural Language Processing Academic Medical Centers New York City Humans Algorithms
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Development and validation of a machine learning model to predict mortality risk in patients with COVID-19.

BMJ health & care informatics May 1, 2021
New York City quickly became an epicentre of the COVID-19 pandemic. An ability to triage patients was needed due to a sudden and massive increase in patients during the COVID-19 pandemic as healthcare providers incurred an exponential increase in wor...
Forecasting Retrospective Studies SARS-CoV-2 Risk Assessment Machine Learning COVID-19 Algorithms Hospital Mortality New York City Humans
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Using Clinical Notes and Natural Language Processing for Automated HIV Risk Assessment.

Journal of acquired immune deficiency syndromes (1999) Feb 1, 2018
OBJECTIVE: Universal HIV screening programs are costly, labor intensive, and often fail to identify high-risk individuals. Automated risk assessment methods that leverage longitudinal electronic health records (EHRs) could catalyze targeted screening...
Decision Support Techniques Electronic Health Records Female Infant, Newborn HIV Infections Risk Factors Middle Aged Humans Cohort Studies Young Adult Aged Risk Assessment Mass Screening Child, Preschool Algorithms Adult Aged, 80 and over Infant Natural Language Processing Child Male Adolescent Automation New York City
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