Surveillance

Development of a hybrid hydrogel for submucosal injection in endoscopic resection of gastrointestinal neoplasm: From laboratory to clinical trial.

Submucosal injection solution is essential for successful endoscopic resection of the early gastroi...

Validation of a Natural Language Machine Learning Model for Safety Literature Surveillance.

INTRODUCTION: As part of routine safety surveillance, thousands of articles of potential interest ar...

Clinical Applications, Methodology, and Scientific Reporting of Electrocardiogram Deep-Learning Models: A Systematic Review.

BACKGROUND: The electrocardiogram (ECG) is one of the most common diagnostic tools available to asse...

Leveraging automated approaches to categorize birth defects from abstracted birth hospitalization data.

BACKGROUND: The Surveillance for Emerging Threats to Pregnant People and Infants Network (SET-NET) c...

Plant disease identification using contextual mask auto-encoder optimized with dynamic differential annealed optimization algorithm.

Most of the food consumed worldwide is produced by plants. Plant disease is a major cause of reduced...

Superior Auto-Identification of Trypanosome Parasites by Using a Hybrid Deep-Learning Model.

Trypanosomiasis is a significant public health problem in several regions across the world, includin...

AI (Artificial Intelligence) as an IA (Intelligent Assistant): ChatGPT for Surveillance Colonoscopy Questions.

Epidemiology of osteoarthritis: literature update 2022-2023.

PURPOSE OF REVIEW: This review highlights recently published studies on osteoarthritis (OA) epidemio...

Robotic-assisted benign hysterectomy compared with laparoscopic, vaginal, and open surgery: a systematic review and meta-analysis.

The potential benefits and limitations of benign hysterectomy surgical approaches are still debated....

Sooty Mold Detection on Citrus Tree Canopy Using Deep Learning Algorithms.

Sooty mold is a common disease found in citrus plants and is characterized by black fungi growth on ...

Influenza Epidemic Trend Surveillance and Prediction Based on Search Engine Data: Deep Learning Model Study.

BACKGROUND: Influenza outbreaks pose a significant threat to global public health. Traditional surve...

Identifying Potential Lyme Disease Cases Using Self-Reported Worldwide Tweets: Deep Learning Modeling Approach Enhanced With Sentimental Words Through Emojis.

BACKGROUND: Lyme disease is among the most reported tick-borne diseases worldwide, making it a major...

Deep Learning-Based Automated Labeling of Coronary Segments for Structured Reporting of Coronary Computed Tomography Angiography in Accordance With Society of Cardiovascular Computed Tomography Guidelines.

PURPOSE: To evaluate a novel deep learning (DL)-based automated coronary labeling approach for struc...

Early monitoring-to-warning Internet of Things system for emerging infectious diseases via networking of light-triggered point-of-care testing devices.

Early monitoring and warning arrangements are effective ways to distinguish infectious agents and co...

From data to insights: how natural language processing and structured reporting advance data-driven radiology.

Confound-leakage: confound removal in machine learning leads to leakage.

BACKGROUND: Machine learning (ML) approaches are a crucial component of modern data analysis in many...

Comparative Effectiveness Analysis of Lumpectomy and Mastectomy for Elderly Female Breast Cancer Patients: A Deep Learning-based Big Data Analysis.

: To evaluate the comparative effectiveness of treatments, a randomized clinical trial remains the g...

An Interventional Radiologist's Primer of Critical Appraisal of Artificial Intelligence Research.

Recent advances in artificial intelligence (AI) are expected to cause a significant paradigm shift i...

Self-reporting with checklists in artificial intelligence research on medical imaging: a systematic review based on citations of CLAIM.

OBJECTIVE: To evaluate the usage of a well-known and widely adopted checklist, Checklist for Artific...

Detailed reporting of clinical and pathological parameters, and comprehensive depiction of complication-intervention events and grading is required to ensure comparability of survival and morbidity outcomes.

Enhanced phenotypes for identifying opioid overdose in emergency department visit electronic health record data.

BACKGROUND: Accurate identification of opioid overdose (OOD) cases in electronic healthcare record (...