Search Articles

View query in Help articles search

Search Results (1 to 5 of 5 Results)

Download search results: CSV END BibTex RIS


Comparison of Deep Learning Approaches Using Chest Radiographs for Predicting Clinical Deterioration: Retrospective Observational Study

Comparison of Deep Learning Approaches Using Chest Radiographs for Predicting Clinical Deterioration: Retrospective Observational Study

Because respiratory failure is a common cause of clinical deterioration, the use of computer vision models with chest radiographs is a promising direction for improving EWS performance [9]. Although traditional computer vision models have historically been used to analyze chest radiographs, prior work on chest radiographs is limited to identifying specific diagnoses [10-12].

Mahmudur Rahman, Jifan Gao, Kyle A Carey, Dana P Edelson, Askar Afshar, John W Garrett, Guanhua Chen, Majid Afshar, Matthew M Churpek

JMIR AI 2025;4:e67144

The Role of Clinician-Developed Applications in Promoting Adherence to Evidence-Based Guidelines: Pilot Study

The Role of Clinician-Developed Applications in Promoting Adherence to Evidence-Based Guidelines: Pilot Study

Chest pain is among the most common emergency department (ED) presentations in New South Wales [10], and acute coronary syndrome is an important differential diagnosis, with high morbidity and mortality. Several evidence-based guidelines for the assessment of chest pain have been introduced to facilitate timely diagnosis and treatment while standardizing practice across various health care facilities [11].

Madhu Prita Prakash, Aravinda Thiagalingam

JMIR Cardio 2024;9:e55958

Consensus Between Radiologists, Specialists in Internal Medicine, and AI Software on Chest X-Rays in a Hospital-at-Home Service: Prospective Observational Study

Consensus Between Radiologists, Specialists in Internal Medicine, and AI Software on Chest X-Rays in a Hospital-at-Home Service: Prospective Observational Study

The basic chest x-ray serves as the cornerstone for the initial diagnosis of many acute conditions, mainly for patients presenting with acute shortness of breath. Nevertheless, its interpretation is subject to a high level of interobserver variability [14]. The application of chest x-rays in patients with suspected community-acquired pneumonia is commonly practiced, although various guidelines and reviews offer differing approaches toward this practice and interpretive value [15].

Eitan Grossbard, Yehonatan Marziano, Adam Sharabi, Eliyahu Abutbul, Aya Berman, Reut Kassif-Lerner, Galia Barkai, Hila Hakim, Gad Segal

JMIR Form Res 2024;8:e55916

Evaluation of GPT-4’s Chest X-Ray Impression Generation: A Reader Study on Performance and Perception

Evaluation of GPT-4’s Chest X-Ray Impression Generation: A Reader Study on Performance and Perception

To generate and evaluate impressions of chest x-rays based on different input modalities (image, text, text and image), a blinded radiological report was written for 25 cases from a publicly available National Institutes of Health data set [10]. The GPT-4 model was given an image, the results, or both sequentially to generate an input-dependent impression.

Sebastian Ziegelmayer, Alexander W Marka, Nicolas Lenhart, Nadja Nehls, Stefan Reischl, Felix Harder, Andreas Sauter, Marcus Makowski, Markus Graf, Joshua Gawlitza

J Med Internet Res 2023;25:e50865

Intervention in the Timeliness of Two Electrocardiography Types for Patients in the Emergency Department With Chest Pain: Randomized Controlled Trial

Intervention in the Timeliness of Two Electrocardiography Types for Patients in the Emergency Department With Chest Pain: Randomized Controlled Trial

Twelve-lead electrocardiography (ECG) is an essential diagnostic tool in the emergency department (ED) for patients with chest pain [1]. The most important step to be taken for a patient who complains of chest pain is to identify the location of the pain. ECG should be performed to determine if the pain is caused by a cardiovascular disease [2].

Suyoung Yoo, Hansol Chang, Taerim kim, Hee yoon, Sung Yeon Hwang, Tae Gun Shin, Min Seob Sim, Ik joon Jo, Jin-Ho Choi, Won Chul Cha

Interact J Med Res 2022;11(2):e36335