A5025454792- ECG Monitoring and Analysis
- Atrial Fibrillation Management and Outcomes
- Oil and Gas Production Techniques
- Drilling and Well Engineering
- Hydraulic Fracturing and Reservoir Analysis
- Pharmaceutical Economics and Policy
- Artificial Intelligence in Healthcare and Education
- Cardiovascular Health and Risk Factors
- Health Systems, Economic Evaluations, Quality of Life
Dokuz Eylül University
2023-2024
Seton Medical Center
2024
Colorado School of Mines
1998
<sec> <title>BACKGROUND</title> Chat Generative Pre-Trained Transformer (ChatGPTTM) is a large language model (LLM)-based chatbot developed by OpenAITM. ChatGPT has many potential applications to healthcare, including enhanced diagnostic accuracy and efficiency, improved treatment planning, better patient outcomes. Healthcare professionals’ perceptions of similar artificial intelligence tools are not well known, understanding these attitudes important inform the best approaches explore their...
Background: Racial and socioeconomic disparities in healthcare access are well-documented. Minority rural populations face barriers often have limited to services facilities. Digital health solutions can help bridge these gaps. Previous studies examining digital usage patterns reported mixed findings, with some showing lower adoption among minority/underserved groups others finding no significant differences compared the general population. Hypothesis: patients would participate intervention...
Background: Atrial fibrillation (AF) is the most common heart rhythm disorder and often requires inpatient monitoring for antiarrhythmic drug (AAD) initiation, specifically dofetilide sotalol. No system currently offers safe at-home AAD which needed to expand access low-risk or underserved patients reduce mortality. Objective: Assess accuracy of dosing using a computer-guided decision tree algorithm compared physician decisions. Methods: Patients in an all-comer population were instructed...
Introduction: We tested the first novel software application to accurately measure QTc using a machine learning algorithm from mobile ECG and recommend patient-specific antiarrhythmic drug (AAD) dosing. The was developed address disparities in AAD hospitalizations that disproportionately affect minority patients. evaluated usability of interface validated Post-Study System Usability Questionnaire (PSSUQ) Health App (MAUQ). Methods: Ten medical providers, 16 clinic staff, patients for remote...
A Computationally Efficient, Transient-Pressure Solution for Inclined Wells E. Ozkan; Ozkan Colorado School of Mines Search other works by this author on: This Site Google Scholar R. Raghavan Phillips Petroleum Company Paper presented at the SPE Annual Technical Conference and Exhibition, New Orleans, Louisiana, September 1998. Number: SPE-49085-MS https://doi.org/10.2118/49085-MS Published: 27 1998 Cite View Citation Add to Manager Share Icon Twitter LinkedIn Get Permissions Ozkan, E.,...