AIMC Topic: Boston

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Exploring the social life of urban spaces through AI.

Proceedings of the National Academy of Sciences of the United States of America Jul 24, 2025
We analyze changes in pedestrian behavior over a 30-y period in four urban public spaces located in New York, Boston, and Philadelphia. Building on William Whyte's observational work, which involved manual video analysis of pedestrian behaviors, we e...
Walking Pedestrians Philadelphia Humans Boston Artificial Intelligence Cities Urban Population
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Data-driven nutritional assessment of urban food landscapes: insights from Boston, London, and Dubai.

Scientific reports Jul 8, 2025
Urban food landscapes significantly influence dietary habits and health outcomes, with disparities in food access contributing to obesity, particularly in socioeconomically disadvantaged neighborhoods. This study presents a data-driven approach to as...
Feeding Behavior London Boston Restaurants Urban Population Residence Characteristics Obesity Food Supply Humans Nutrition Assessment Socioeconomic Factors
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Clinician Attitudes and Perceptions of Point-of-Care Information Resources and Their Integration Into Electronic Health Records: Qualitative Interview Study.

JMIR medical informatics May 26, 2025
BACKGROUND: Electronic health records (EHRs) are widely used in health care systems across the United States to help clinicians access patient medical histories in one central location. As medical knowledge expands, clinicians are increasingly using ...
Middle Aged Boston Qualitative Research Female Humans Attitude of Health Personnel Adult Electronic Health Records Interviews as Topic Male Point-of-Care Systems
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Alternative stopping rules to limit tree expansion for random forest models.

Scientific reports Sep 6, 2022
Random forests are a popular type of machine learning model, which are relatively robust to overfitting, unlike some other machine learning models, and adequately capture non-linear relationships between an outcome of interest and multiple independen...
Machine Learning Nutrition Surveys Los Angeles Boston
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Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Identify and Estimate Survival in a Longitudinal Cohort of Patients With Lung Cancer.

JAMA network open Jul 1, 2021
IMPORTANCE: Electronic health records (EHRs) provide a low-cost means of accessing detailed longitudinal clinical data for large populations. A lung cancer cohort assembled from EHR data would be a powerful platform for clinical outcome studies.
Electronic Health Records Female Male Cohort Studies Humans Machine Learning Algorithms Prognosis Survivors Boston ROC Curve Lung Neoplasms Area Under Curve Survival Analysis
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Assessment of the Acceptability and Feasibility of Using Mobile Robotic Systems for Patient Evaluation.

JAMA network open Mar 1, 2021
IMPORTANCE: Before the widespread implementation of robotic systems to provide patient care during the COVID-19 pandemic occurs, it is important to understand the acceptability of these systems among patients and the economic consequences associated ...
Humans Pandemics COVID-19 Delivery of Health Care Female Aged Adult Patient Care Surveys and Questionnaires Male Feasibility Studies Triage Middle Aged Catheterization Telemedicine Robotics Hospitals Phlebotomy Patient Satisfaction Emergency Service, Hospital Physical Examination Boston
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Development and Validation of a Deep Learning Model for Detection of Allergic Reactions Using Safety Event Reports Across Hospitals.

JAMA network open Nov 2, 2020
IMPORTANCE: Although critical to patient safety, health care-related allergic reactions are challenging to identify and monitor.
Humans Algorithms Hypersensitivity Middle Aged Patient Safety Diagnosis, Computer-Assisted Aged Boston Female Deep Learning Adult Reproducibility of Results ROC Curve Cross-Sectional Studies Male
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Machine learning provides evidence that stroke risk is not linear: The non-linear Framingham stroke risk score.

PloS one May 21, 2020
Current stroke risk assessment tools presume the impact of risk factors is linear and cumulative. However, both novel risk factors and their interplay influencing stroke incidence are difficult to reveal using traditional additive models. The goal of...
Prospective Studies Nonlinear Dynamics Female Models, Cardiovascular Risk Factors Boston Aged Humans Machine Learning Algorithms Electrocardiography Male Decision Trees Middle Aged Stroke Risk Assessment Hematocrit Cohort Studies
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Prediction of microbial communities for urban metagenomics using neural network approach.

Human genomics Oct 22, 2019
BACKGROUND: Microbes are greatly associated with human health and disease, especially in densely populated cities. It is essential to understand the microbial ecosystem in an urban environment for cities to monitor the transmission of infectious dise...
Databases, Genetic Neural Networks, Computer Boston Algorithms Microbiota Reproducibility of Results Metagenomics Cities New York Models, Genetic
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Deep learning algorithms to identify documentation of serious illness conversations during intensive care unit admissions.

Palliative medicine Nov 14, 2018
Intensive Care Units Middle Aged Humans Guidelines as Topic Female Deep Learning Boston Algorithms Adult Critical Care Health Personnel Admitting Department, Hospital Male Documentation
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