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Implementation and Evaluation of an Offline RPA-Based Scheduling Visualization Tool for Radiotherapy Under Security Constraints
Implementation and Evaluation of an Offline RPA-Based Scheduling Visualization Tool for Radiotherapy Under Security Constraints
Timely access to radiotherapy appointment information remains challenging in hospitals—including many in Japan—...
Integrating mHealth Innovations into Decentralized Oncology Trials
Integrating mHealth Innovations into Decentralized Oncology Trials
The integration of mobile health (mHealth) technologies into decentralized clinical trials (DCTs) may represent a paradigm...
An Exploratory Comparison of AI Models for Preoperative Anesthesia Planning: Assessing ChatGPT-4o, Claude 3.5 Sonnet, and ChatGPT-o1 in Clinical Scenario Analysis
An Exploratory Comparison of AI Models for Preoperative Anesthesia Planning: Assessing ChatGPT-4o, Claude 3.5 Sonnet, and ChatGPT-o1 in Clinical Scenario Analysis
This exploratory study examined the effectiveness of ChatGPT-4o, Claude 3.5 Sonnet, and ChatGPT-o1 in developing anesthesi...
Nurse Staffing Management in the Context of Emergency Departments and Seasonal Respiratory Diseases: An Artificial Intelligence and Discrete-Event Simulation Approach
Nurse Staffing Management in the Context of Emergency Departments and Seasonal Respiratory Diseases: An Artificial Intelligence and Discrete-Event Simulation Approach
Emergency Departments (EDs) usually experience nursing shortages during Seasonal Respiratory Diseases (SRDs). As a result,...
Automated Characterization of Sudden Cardiac Death Using Locality Preserving Projection and Fuzzy Entropy Based on Empirical Mode Decomposition from ECG Signals
Automated Characterization of Sudden Cardiac Death Using Locality Preserving Projection and Fuzzy Entropy Based on Empirical Mode Decomposition from ECG Signals
The early prediction of sudden cardiac death (SCD) has garnered considerable global attention as a potentially life-saving...
Symptom Recognition in Medical Conversations Via multi- Instance Learning and Prompt
Symptom Recognition in Medical Conversations Via multi- Instance Learning and Prompt
With the widespread adoption of electronic health record (EHR) systems, there is a crucial need for automatic extraction o...
Applying the Model for Assessing the Value of AI (MAS-AI) Framework To Organizational AI: A Case Study of Surgical Scheduling Assessment in Italy
Applying the Model for Assessing the Value of AI (MAS-AI) Framework To Organizational AI: A Case Study of Surgical Scheduling Assessment in Italy
This work aims to explore the transferability of the Model for Assessing the value of Artificial Intelligence in medical i...
Smartphone-Based Digital Health Interventions: A Comprehensive Systematic Review of Efficacy for Cardiovascular and Cerebrovascular Outcomes
Smartphone-Based Digital Health Interventions: A Comprehensive Systematic Review of Efficacy for Cardiovascular and Cerebrovascular Outcomes
Digital health interventions (DHIs) have the potential to transform the management of cardiovascular disease (CVD) and cer...
How Well Do ChatGPT and Claude Perform in Study Selection for Systematic Review in Obstetrics
How Well Do ChatGPT and Claude Perform in Study Selection for Systematic Review in Obstetrics
The use of generative AI in systematic review workflows has gained attention for enhancing study selection efficiency. How...
Empowering Cancer Patients: A Scoping Review on Gamified Approaches To Health Literacy for Self-Care
Empowering Cancer Patients: A Scoping Review on Gamified Approaches To Health Literacy for Self-Care
To address the challenges of self-care in oncology, gamification emerges as an innovative strategy to enhance health liter...
Prediction Model of Intradialytic Hypertension in Hemodialysis Patients Based on Machine Learning
Prediction Model of Intradialytic Hypertension in Hemodialysis Patients Based on Machine Learning
The escalating global burden of chronic kidney disease (CKD), particularly end-stage renal disease (ESRD), has intensified...
Bimodal ECG and PCG Cardiovascular Disease Detection: Exploring the Potential and Modality Contribution
Bimodal ECG and PCG Cardiovascular Disease Detection: Exploring the Potential and Modality Contribution
Early detection of cardiovascular diseases (CVDs) is crucial for improving patient outcomes and alleviating healthcare bur...
Large Language Models in Neurology Treatment Decision-Making: a Scoping Review
Large Language Models in Neurology Treatment Decision-Making: a Scoping Review
This scoping review evaluates the expanding role of large language models (LLMs) in neurology, an area drawing growing int...
Social Network Analysis of Secure Text Messaging Metadata During Clinical Deterioration in an Inpatient Children’s Hospital Setting
Social Network Analysis of Secure Text Messaging Metadata During Clinical Deterioration in an Inpatient Children’s Hospital Setting
Mitigating clinical deterioration relies upon recognition (afferent limb) and interventions (efferent limb) by a healthcar...
Integrating Pediatric Anesthesia Sustainability Metrics into Native Electronic Health Records: A Clinical Informatics Approach
Integrating Pediatric Anesthesia Sustainability Metrics into Native Electronic Health Records: A Clinical Informatics Approach
The growing emphasis on sustainability in healthcare has highlighted anesthetic gases as notable contrib utors to th...
Automated Resectability Classification of Pancreatic Cancer CT Reports with Privacy-Preserving Open-Weight Large Language Models: A Multicenter Study
Automated Resectability Classification of Pancreatic Cancer CT Reports with Privacy-Preserving Open-Weight Large Language Models: A Multicenter Study
Purpose. To evaluate the effectiveness of open-weight large language models (LLMs) in extracting key radiological...
Enhancing Patient Identification Accuracy in Shared Child Health Records: a Hybrid Approach for the Lao Language Context
Enhancing Patient Identification Accuracy in Shared Child Health Records: a Hybrid Approach for the Lao Language Context
The Shared Child Health Record (SCHR) project in Lao People’s Democratic Republic (PDR) aims to enhance pediatric he...
A Pretraining Approach for Small-sample Training Employing Radiographs (PASTER): a Multimodal Transformer Trained by Chest Radiography and Free-text Reports
A Pretraining Approach for Small-sample Training Employing Radiographs (PASTER): a Multimodal Transformer Trained by Chest Radiography and Free-text Reports
While deep convolutional neural networks (DCNNs) have achieved remarkable performance in chest X-ray interpretation, their...
Clinical Risk Computation by Large Language Models Using Validated Risk Scores
Clinical Risk Computation by Large Language Models Using Validated Risk Scores
Recent advances in artificial intelligence have propelled Large Language Models (LLMs) in natural language understanding, ...
Influence of Practitioner Dashboard Feedback on Anesthetic Greenhouse Gas Emissions: A Prospective Performance Improvement Investigation
Influence of Practitioner Dashboard Feedback on Anesthetic Greenhouse Gas Emissions: A Prospective Performance Improvement Investigation
Anesthetic gases contribute to global warming. We described a two-year performance improvement project to examine the asso...
Effectiveness of Mobile Health Intervention in Medication Adherence: a Systematic Review and Meta-Analysis
Effectiveness of Mobile Health Intervention in Medication Adherence: a Systematic Review and Meta-Analysis
Low medication adherence poses a great risk of poor treatment outcomes among patients with chronic diseases. Recently, mob...
Assessing the Efficacy of ChatGPT Prompting Strategies in Enhancing Thyroid Cancer Patient Education: A Prospective Study
Assessing the Efficacy of ChatGPT Prompting Strategies in Enhancing Thyroid Cancer Patient Education: A Prospective Study
With the rise of AI platforms, patients increasingly use them for information, relying on advanced language models like Ch...
Development and Implementation of Automated Referral Triaging System for Spinal Cord Stimulation Procedure in Pain Medicine
Development and Implementation of Automated Referral Triaging System for Spinal Cord Stimulation Procedure in Pain Medicine
Effective referral triaging enhances patient service outcomes, experience and access to care especially for specialized pr...
Evaluating Large Language Models for Automated CPT Code Prediction in Endovascular Neurosurgery
Evaluating Large Language Models for Automated CPT Code Prediction in Endovascular Neurosurgery
Large language models (LLMs) have been utilized to automate tasks like writing discharge summaries and operative reports i...
Development of Attention-based Prediction Models for All-cause Mortality, Home Care Need, and Nursing Home Admission in Ageing Adults in Spain Using Longitudinal Electronic Health Record Data
Development of Attention-based Prediction Models for All-cause Mortality, Home Care Need, and Nursing Home Admission in Ageing Adults in Spain Using Longitudinal Electronic Health Record Data
Predicting health-related outcomes can help with proactive healthcare planning and resource management. This is especially...
Ensuring Medical Device Safety: The Role of Standards Organizations and Regulatory Bodies
Ensuring Medical Device Safety: The Role of Standards Organizations and Regulatory Bodies
Medical devices significantly enhance healthcare by integrating advanced technology to improve patient outcomes. Ensuring ...
Mobile Applications for Longitudinal Data Collection: Web-based Survey Study of Former Intensive Care Patients
Mobile Applications for Longitudinal Data Collection: Web-based Survey Study of Former Intensive Care Patients
Purpose: Mobile health plays an important role in providing individualized information about the health status of patients...
Prediction of the Risk of Adverse Clinical Outcomes with Machine Learning Techniques in Patients with Noncommunicable Diseases
Prediction of the Risk of Adverse Clinical Outcomes with Machine Learning Techniques in Patients with Noncommunicable Diseases
Decision-making in chronic diseases guided by clinical decision support systems that use models including multiple variabl...
Using the Nudge Theory to Enhance Attending Anesthesiologist Breaks
Using the Nudge Theory to Enhance Attending Anesthesiologist Breaks
It is well understood that human behavior can be influenced, often by the most subtle of factors. Otherwise known as ̶...
Deep Learning Radiomics for Survival Prediction in Non-Small-Cell Lung Cancer Patients from CT Images
Deep Learning Radiomics for Survival Prediction in Non-Small-Cell Lung Cancer Patients from CT Images
This study aims to apply a multi-modal approach of the deep learning method for survival prediction in patients with non-s...
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