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NYU Dataset
Neurological Emergencies Outcomes at NYU
- Alternate Title(s)
- NEON
- Authors
- Ariane LewisAaron Lord
- Description
This dataset was collected for a combined retrospective and prospective cross-sectional study to establish risk factors for infection after treatment for intracerebral hemorrhage and subarachnoid hemorrhage and to determine the impact of those infections on long-term outcomes. Data was harvested from Tisch Hospital records from January 2013 to December 2014 retrospectively and from January 2015 to...
- Subject
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Electronic Health RecordsNeuroscienceRisk Factors
- Access Rights
- Application RequiredAuthor Approval Required
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NYU Dataset
Memory performance data as measured by acute and chronic intracranial EEG
- Authors
- Simon HeninAnita ShankarNicholas HasulakDaniel Friedman10 more author(s)...
- Description
This dataset was collected for a study to replicate previous work on hippocampal physiology predictive of successful encoding using an associative memory paradigm in a surgical intracranial electroencephalography (iEEG) group and extend those investigations to a chronic ambulatory iEEG population using RNS System devices (NeuroPace, Inc.). The primary objective was to compare the hippocampal gamma...
- Subject
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Chronic DiseaseElectronic Health RecordsNeuroscience
- Access Rights
- Application RequiredAuthor Approval Required
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National COVID Cohort Collaborative Data Enclave
- Alternate Title(s)
- N3C Data Enclave
- Description
The National Center for Advancing Translational Sciences (NCATS) has systematically compiled clinical, laboratory and diagnostic data from electronic health records to support COVID-19 research efforts via the National COVID Cohort Collaborative (N3C) Data Enclave. As of August 2, 2022, the repository contains information from over 15 million patients (including 5.8 million COVID-19 positive patients)...
- Subject
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COVID-19Electronic Health RecordsHealth Care SystemHealth StatusInfectious DiseasePopulation CharacteristicsRisk Factors
- Access Rights
- Free to AllApplication Required
- Local Expert
- Silvia Curado
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All of Us Research Hub
- Description
With an emphasis on reaching historically underrepresented populations, the All of Us Research Program recruits adults aged 18 and above across the United States to share their health data to enable new insights into human health and research on precision medicine. Participants contribute electronic health records (EHR), survey responses, biospecimens, wearable devices (biometrics), and physical measurements....
- Subject
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COVID-19Electronic Health RecordsGenomicsHealth Care SystemHealth StatusMental HealthPopulation CharacteristicsRisk Factors
- Access Rights
- Application RequiredAll NYU
- Local Expert
- Fred LaPolla
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NYU Dataset
NYUTron: Health System Scale Language Models Are All-purpose Prediction Engines
- Authors
- Lavender Yao JiangXujin Chris LiuNima Pour NejatianMustafa Nasir-Moin24 more author(s)...
- Description
NYUTron is a large language model-based system that was developed with the objective of integrating clinical workflows centered around structured and unstructured notes and placing electronic orders in real time. The development team queried electronic health records from all NYU Langone facilities to generate two types of datasets: pre-training datasets ("NYU Notes", "NYU Notes–Manhattan", "NYU Notes–Brooklyn")...
- Subject
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Electronic Health Records
- Access Rights
- Free to All
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National Health Service Hospital Episode Statistics
- Alternate Title(s)
- NHS HES
- Description
The National Health Service Hospital Episode Statistics (NHS HES) include over 1 billion medical records of patients who attended outpatient appointments, were seen at accident and emergency (A&E) departments, or were admitted to NHS hospitals in England. This data is collected and curated on a monthly basis and has been used for purposes such as research and service evaluation. HES consists of the...
- Subject
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Electronic Health RecordsHealth Care SystemQuality of Health Care
- Access Rights
- Free to AllApplication Required
- Local Expert
- Simon A. Jones
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NYU Dataset
AI Prompts for Physician Note Quality Assessment
- Authors
- Jonah FeldmanKathy HochmanBenedict Vincent GuzmanAdam Goodman2 more author(s)...
- Description
This dataset consists of AI prompts used to improve the content and quality of medical documentation in a case study at NYU Langone Health. Both prompts were used with institutional instance of GPT-4. The first prompt checks for completeness of a clinical note, ensuring that comments from the patients, an all-encompassing description of the patient, a description of the appropriate exam, and an update...
- Subject
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Electronic Health RecordsHealth Care SystemQuality of Health Care
- Access Rights
- Free subject to license
