日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Transatlantic transferability and replicability of machine-learning algorithms to predict mental health crises

跨大西洋机器学习算法在预测心理健康危机方面的可转移性和可复制性

Guerreiro, João; Garriga, Roger; Lozano Bagén, Toni; Sharma, Brihat; Karnik, Niranjan S; Matić, Aleksandar

DR.BENCH: Diagnostic Reasoning Benchmark for Clinical Natural Language Processing

DR.BENCH:临床自然语言处理的诊断推理基准

Gao, Yanjun; Dligach, Dmitriy; Miller, Timothy; Caskey, John; Sharma, Brihat; Churpek, Matthew M; Afshar, Majid

Machine Learning Techniques to Explore Clinical Presentations of COVID-19 Severity and to Test the Association With Unhealthy Opioid Use: Retrospective Cross-sectional Cohort Study

利用机器学习技术探索 COVID-19 严重程度的临床表现并检验其与不健康阿片类药物使用之间的关联:回顾性横断面队列研究

Thompson, Hale M; Sharma, Brihat; Smith, Dale L; Bhalla, Sameer; Erondu, Ihuoma; Hazra, Aniruddha; Ilyas, Yousaf; Pachwicewicz, Paul; Sheth, Neeral K; Chhabra, Neeraj; Karnik, Niranjan S; Afshar, Majid

The Evaluation of a Clinical Decision Support Tool Using Natural Language Processing to Screen Hospitalized Adults for Unhealthy Substance Use: Protocol for a Quasi-Experimental Design

利用自然语言处理技术评估临床决策支持工具在筛查住院成人不健康物质使用方面的应用:准实验设计方案

Joyce, Cara; Markossian, Talar W; Nikolaides, Jenna; Ramsey, Elisabeth; Thompson, Hale M; Rojas, Juan C; Sharma, Brihat; Dligach, Dmitriy; Oguss, Madeline K; Cooper, Richard S; Afshar, Majid

Publicly available machine learning models for identifying opioid misuse from the clinical notes of hospitalized patients

公开可用的机器学习模型,用于从住院患者的临床记录中识别阿片类药物滥用情况

Sharma, Brihat; Dligach, Dmitriy; Swope, Kristin; Salisbury-Afshar, Elizabeth; Karnik, Niranjan S; Joyce, Cara; Afshar, Majid

Differences in length of stay and discharge destination among patients with substance use disorders: The effect of Substance Use Intervention Team (SUIT) consultation service

物质使用障碍患者的住院时长和出院去向差异:物质使用干预小组(SUIT)咨询服务的影响

Thompson, Hale M; Faig, Walter; VanKim, Nicole A; Sharma, Brihat; Afshar, Majid; Karnik, Niranjan S

Development and application of a high throughput natural language processing architecture to convert all clinical documents in a clinical data warehouse into standardized medical vocabularies

开发和应用高吞吐量自然语言处理架构,将临床数据仓库中的所有临床文档转换为标准化的医学词汇表。

Afshar, Majid; Dligach, Dmitriy; Sharma, Brihat; Cai, Xiaoyuan; Boyda, Jason; Birch, Steven; Valdez, Daniel; Zelisko, Suzan; Joyce, Cara; Modave, François; Price, Ron