Comparison of Deep Learning Approaches Using Chest Radiographs for Predicting Clinical Deterioration: Retrospective Observational Study [0.03%]
基于胸部X光片预测临床恶化的深度学习方法比较：回顾性观察研究
Mahmudur Rahman,Jifan Gao,Kyle A Carey et al.
Mahmudur Rahman et al.
Background: The early detection of clinical deterioration and timely intervention for hospitalized patients can improve patient outcomes. The currently existing early warning systems rely on variables from structured data...
Limitations of Binary Classification for Long-Horizon Diagnosis Prediction and Advantages of a Discrete-Time Time-to-Event Approach: Empirical Analysis [0.03%]
长期诊断预测的二元分类局限性及离散时间风险预测优势的实证分析
De Rong Loh,Elliot D Hill,Nan Liu et al.
De Rong Loh et al.
Background: A major challenge in using electronic health records (EHR) is the inconsistency of patient follow-up, resulting in right-censored outcomes. This becomes particularly problematic in long-horizon event predictio...
Estimation of Static Lung Volumes and Capacities From Spirometry Using Machine Learning: Algorithm Development and Validation [0.03%]
基于肺功能测定的机器学习算法估算静态肺容积和肺量：开发与验证
Scott A Helgeson,Zachary S Quicksall,Patrick W Johnson et al.
Scott A Helgeson et al.
Background: Spirometry can be performed in an office setting or remotely using portable spirometers. Although basic spirometry is used for diagnosis of obstructive lung disease, clinically relevant information such as res...
Deep Learning Models to Predict Diagnostic and Billing Codes Following Visits to a Family Medicine Practice: Development and Validation Study [0.03%]
预测初级诊疗就诊后的诊断和账单代码的深度学习模型的研发与验证研究
Akshay Rajaram,Michael Judd,David Barber
Akshay Rajaram
Background: Despite significant time spent on billing, family physicians routinely make errors and miss billing opportunities. In other disciplines, machine learning models have predicted Current Procedural Terminology co...
Using AI to Translate and Simplify Spanish Orthopedic Medical Text: Instrument Validation Study [0.03%]
利用人工智能翻译和简化西班牙语骨科医学文本的仪器验证研究
Saman Andalib,Aidin Spina,Bryce Picton et al.
Saman Andalib et al.
Background: Language barriers contribute significantly to health care disparities in the United States, where a sizable proportion of patients are exclusively Spanish speakers. In orthopedic surgery, such barriers impact ...
AI-Powered Drug Classification and Indication Mapping for Pharmacoepidemiologic Studies: Prompt Development and Validation [0.03%]
基于人工智能的药物分类和适应症映射在药物流行病学研究中的应用：开发与验证
Benjamin Ogorek,Thomas Rhoads,Eric Finkelman et al.
Benjamin Ogorek et al.
Background: Pharmacoepidemiologic studies, which promote rational drug use and improve health outcomes, often require Anatomical Therapeutic Chemical Classification System (ATC) drug classification within real-world data ...
High-Throughput Phenotyping of the Symptoms of Alzheimer Disease and Related Dementias Using Large Language Models: Cross-Sectional Study [0.03%]
基于大规模语言模型的阿尔茨海默病及相关痴呆症症状高通量表型分析：横断面研究
You Cheng,Mrunal Malekar,Yingnan He et al.
You Cheng et al.
Background: Alzheimer disease and related dementias (ADRD) are complex disorders with overlapping symptoms and pathologies. Comprehensive records of symptoms in electronic health records (EHRs) are critical for not only r...
ChatGPT-4-Driven Liver Ultrasound Radiomics Analysis: Advantages and Drawbacks Compared to Traditional Techniques [0.03%]
基于ChatGPT-4的肝超声影像组学分析：与传统技术相比的优势和劣势
Laith Sultan,Shyam Sunder B Venkatakrishna,Sudha Anupindi et al.
Laith Sultan et al.
Background: Artificial intelligence (AI) is transforming medical imaging, with large language models such as ChatGPT-4 emerging as potential tools for automated image interpretation. While AI-driven radiomics has shown pr...
Exploring Patient Participation in AI-Supported Health Care: Qualitative Study [0.03%]
人工智能支持的医疗中患者参与定性研究
Laura Arbelaez Ossa,Michael Rost,Nathalie Bont et al.
Laura Arbelaez Ossa et al.
Background: The introduction of artificial intelligence (AI) into health care has sparked discussions about its potential impact. Patients, as key stakeholders, will be at the forefront of interacting with and being impac...
Correction: Improving the Robustness and Clinical Applicability of Automatic Respiratory Sound Classification Using Deep Learning-Based Audio Enhancement: Algorithm Development and Validation [0.03%]
纠正：使用基于深度学习的音频增强技术改进自动呼吸音分类的鲁棒性和临床适用性：算法开发与验证
Jing-Tong Tzeng,Jeng-Lin Li,Huan-Yu Chen et al.
Jing-Tong Tzeng et al.
[This corrects the article DOI: 10.2196/67239.]. ©Jing-Tong Tzeng, Jeng-Lin Li, Huan-Yu Chen, Chun-Hsiang Huang, Chi-Hsin Chen, Cheng-Yi Fan, Edward Pei...
Published Erratum
JMIR AI. 2025 Apr 29:4:e76150. DOI:10.2196/76150 2025