Surveillance

The endorsement of general and artificial intelligence reporting guidelines in radiological journals: a meta-research study.

BACKGROUND: Complete reporting is essential for clinical research. However, the endorsement of reporting guidelines in radiological journals is still unclear. Further, as a field extensively utilizing artificial intelligence (AI), the adoption of both general and AI reporting guidelines would be necessary for enhancing quality and transparency of radiological research. This study aims to investiga...

Optimizing Signal Management in a Vaccine Adverse Event Reporting System: A Proof-of-Concept with COVID-19 Vaccines Using Signs, Symptoms, and Natural Language Processing.

INTRODUCTION: The Vaccine Adverse Event Reporting System (VAERS) has already been challenged by an extreme increase in the number of individual case safety reports (ICSRs) after the market introduction of coronavirus disease 2019 (COVID-19) vaccines. Evidence from scientific literature suggests that when there is an extreme increase in the number of ICSRs recorded in spontaneous reporting database...

The Potential of AI and ChatGPT in Improving Agricultural Injury and Illness Surveillance Programming and Dissemination.

Generative Artificial Intelligence (AI) provides unprecedented opportunities to improve injury surveillance systems in many ways, including the curati...

The use of ChatGPT in medical research: do we need a reporting guideline?

Crisis averted: a world united against the menace of multiple drug-resistant superbugs -pioneering anti-AMR vaccines, RNA interference, nanomedicine, CRISPR-based antimicrobials, bacteriophage therapies, and clinical artificial intelligence strategies to safeguard global antimicrobial arsenal.

The efficacy of antibiotics and other antimicrobial agents in combating bacterial infections faces a grave peril in the form of antimicrobial resistan...

The Unseen Hand: AI-Based Prescribing Decision Support Tools and the Evaluation of Drug Safety and Effectiveness.

The use of artificial intelligence (AI)-based tools to guide prescribing decisions is full of promise and may enhance patient outcomes. These tools ca...

A Scoping Review of the Use of Robotics Technologies for Supporting Social-Emotional Learning in Children with Autism.

This scoping review synthesises the current research into robotics technologies for promoting social-emotional learning in children with autism spectr...

Advances in melanoma: epidemiology, diagnosis, and prognosis.

Unraveling the multidimensional complexities of melanoma has required concerted efforts by dedicated community of researchers and clinicians battling ...

A systematic review on automated clinical depression diagnosis.

Assessing mental health disorders and determining treatment can be difficult for a number of reasons, including access to healthcare providers. Assess...

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 are manually triaged for review by safety surveillan...

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) collects data abstracted from medical records and b...

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 production, but can be managed with regular monit...

Epidemiology of osteoarthritis: literature update 2022-2023.

PURPOSE OF REVIEW: This review highlights recently published studies on osteoarthritis (OA) epidemiology, including topics related to understudied pop...

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. We aimed at evaluating any differences with a sys...

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 surveillance systems and simple algorithms often strugg...

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 fruits, leaves, and branches. This mold reduces th...

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 ongoing public health concern. An effective Lyme ...

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 structured reporting of coronary artery disease accordi...

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 control the spread of epidemic diseases. Current tes...

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 fields, including epidemiology and medicine. Nonl...