AIMC Topic: Massachusetts
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Automated Extraction of Stroke Severity From Unstructured Electronic Health Records Using Natural Language Processing.
Journal of the American Heart Association
Oct 25, 2024
BACKGROUND: Multicenter electronic health records can support quality improvement and comparative effectiveness research in stroke. However, limitations of electronic health record-based research include challenges in abstracting key clinical variabl...
A neural network solves, explains, and generates university math problems by program synthesis and few-shot learning at human level.
Proceedings of the National Academy of Sciences of the United States of America
Aug 2, 2022
We demonstrate that a neural network pretrained on text and fine-tuned on code solves mathematics course problems, explains solutions, and generates questions at a human level. We automatically synthesize programs using few-shot learning and OpenAI's...
Development and Validation of a Deep Learning Model for Earlier Detection of Cognitive Decline From Clinical Notes in Electronic Health Records.
JAMA network open
Nov 1, 2021
IMPORTANCE: Detecting cognitive decline earlier among older adults can facilitate enrollment in clinical trials and early interventions. Clinical notes in longitudinal electronic health records (EHRs) provide opportunities to detect cognitive decline...
Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic.
Healthcare (Amsterdam, Netherlands)
Oct 26, 2020
The COVID-19 pandemic has created unique challenges for the U.S. healthcare system due to the staggering mismatch between healthcare system capacity and patient demand. The healthcare industry has been a relatively slow adopter of digital innovation ...
Identification of suicidal behavior among psychiatrically hospitalized adolescents using natural language processing and machine learning of electronic health records.
PloS one
Feb 19, 2019
OBJECTIVE: The rapid proliferation of machine learning research using electronic health records to classify healthcare outcomes offers an opportunity to address the pressing public health problem of adolescent suicidal behavior. We describe the devel...
Screening pregnant women for suicidal behavior in electronic medical records: diagnostic codes vs. clinical notes processed by natural language processing.
BMC medical informatics and decision making
May 29, 2018
BACKGROUND: We examined the comparative performance of structured, diagnostic codes vs. natural language processing (NLP) of unstructured text for screening suicidal behavior among pregnant women in electronic medical records (EMRs).
A spatio-temporal prediction model based on support vector machine regression: Ambient Black Carbon in three New England States.
Environmental research
Sep 18, 2017
Fine ambient particulate matter has been widely associated with multiple health effects. Mitigation hinges on understanding which sources are contributing to its toxicity. Black Carbon (BC), an indicator of particles generated from traffic sources, h...
Assessing Hospital Performance After Percutaneous Coronary Intervention Using Big Data.
Circulation. Cardiovascular quality and outcomes
Nov 8, 2016
BACKGROUND: Although risk adjustment remains a cornerstone for comparing outcomes across hospitals, optimal strategies continue to evolve in the presence of many confounders. We compared conventional regression-based model to approaches particularly ...
Likelihood Functions
Massachusetts
Process Assessment, Health Care
Middle Aged
Data Mining
Humans
Female
Logistic Models
Hospitals
Quality Indicators, Health Care
Risk Factors
Treatment Outcome
Machine Learning
Time Factors
Multivariate Analysis
Aged
Algorithms
Hospital Mortality
Propensity Score
Aged, 80 and over
Cause of Death
Databases, Factual
Male
Registries
Percutaneous Coronary Intervention
Predicting early psychiatric readmission with natural language processing of narrative discharge summaries.
Translational psychiatry
Oct 18, 2016
The ability to predict psychiatric readmission would facilitate the development of interventions to reduce this risk, a major driver of psychiatric health-care costs. The symptoms or characteristics of illness course necessary to develop reliable pre...
Early Experience of Robot-Assisted Esophagectomy With Circular End-to-End Stapled Anastomosis.
The Annals of thoracic surgery
May 4, 2016
BACKGROUND: Surgical resection is a critical element in the treatment of esophageal cancer. Esophagectomy is technically challenging and is associated with high morbidity and mortality rates. Efforts to reduce these rates have spurred the adoption of...
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