Surveys

Standardization and accuracy of race and ethnicity data: Equity implications for medical AI.

The rapid integration of artificial intelligence (AI) into healthcare has raised many concerns about race bias in AI models. Yet, overlooked in this dialogue is the lack of quality control for the accuracy of patient race and ethnicity (r/e) data in electronic health records (EHR). This article critically examines the factors driving inaccurate and unrepresentative r/e datasets. These include conc...

Gas sensors and real-time video for accurate classroom occupancy detection.

This study introduces an advanced methodology for optimizing HVAC efficiency through real-time classroom occupancy detection by combining video analysis with gas sensor data to enhance accuracy and reliability. The proposed system integrates video feeds captured by a Logitech C20 webcam with data from an MS1100 gas sensor module, ensuring a dual-modal approach to occupancy detection. A YOLOv4 obje...

Impact of analytical bias on machine learning models for sepsis prediction using laboratory data.

OBJECTIVES: Machine learning (ML) models, using laboratory data, support early sepsis prediction. However, analytical bias in laboratory measurements ...

Mitigating medical dataset bias by learning adaptive agreement from a biased council.

Dataset bias in images is an important yet less explored topic in medical images. Deep learning could be prone to learning spurious correlation raised...

Clinical validation of a proposed diagnostic classification for pulpitis.

AIM: Determine the reliability and clinical validity of the Wolters classification of pulpitis.

Immunogenic cell death biomarkers for sepsis diagnosis and mechanism via integrated bioinformatics.

Immunogenic cell death (ICD) has been implicated in sepsis, a condition with high mortality, through mechanisms involving endoplasmic reticulum stress...

Smart intrusion detection model to identify unknown attacks for improved road safety and management.

The Internet of Vehicles (IoV) has emerged as a transformative technology for intelligent transportation systems, enabling real-time communication bet...

From development to implementation: a systematic review on the current maturity status of artificial intelligence models for patients with colorectal cancer liver metastases.

Introduction Artificial intelligence (AI) is increasingly being researched and developed in the medical field and holds potential to transform healthc...

Validity and Reliability of an Artificial Intelligence-Based Posture Estimation Software for Measuring Cervical and Lower-Limb Alignment Versus Radiographic Imaging.

: Accurate postural assessment is essential for managing musculoskeletal disorders; however, routine screening is often limited by radiation exposure,...

Mitigating patient harm risks: A proposal of requirements for AI in healthcare.

With the rise Artificial Intelligence (AI), mitigation strategies may be needed to integrate AI-enabled medical software responsibly, ensuring ethical...

Optimizing Treatment for Depression in Primary Care Using Psychotherapy Versus Antidepressant Medication in a Low-Resource Setting: Protocol for the OptimizeD Randomized Controlled Trial.

Psychotherapy and antidepressant medications are first-line treatments for depression, and they both have significant treatment effects on average. H...

Public views on research with publicly available data in Switzerland: Implications for digital research, science communication, and policy.

The increasing volume of publicly available data brought about by digitalization offers researchers opportunities to examine public sentiment on vario...

The effect of selection bias on the performance of a deep learning-based intraoperative hypotension prediction model using real-world samples from a publicly available database.

BACKGROUND: There are models to predict intraoperative hypotension from arterial pressure waveforms. Selection bias in datasets used for model develop...

The Role of Artificial Intelligence in Chronic Liver Diseases and Liver Transplantation.

In hepatology, pattern recognition in laboratory data and clinical characteristics is the hallmark of clinical care. Artificial intelligence (AI) tool...

Diagnostic Accuracy of Machine Learning-Assisted MRI for Mild Cognitive Impairment in Parkinson's Disease: A Systematic Review and Meta-Analysis.

To evaluate the diagnostic accuracy of machine learning-assisted magnetic resonance imaging (MRI) in detecting cognitive impairment among Parkinson's ...

Solubility prediction of edible insect proteins: A comparative study of machine learning and response surface methodology.

This study evaluated whether machine learning models could offer improved predictive performance over traditional response surface methodology (RSM) i...

Radiomics and AI-Based Prediction of MGMT Methylation Status in Glioblastoma Using Multiparametric MRI: A Hybrid Feature Weighting Approach.

: Glioblastoma (GBM) is a highly aggressive primary central nervous system tumor with a median survival of 14 months. MGMT (O6-methylguanine-DNA methy...

Assessing the Accuracy and Reliability of Large Language Models in Psychiatry Using Standardized Multiple-Choice Questions: Cross-Sectional Study.

BACKGROUND: Large language models (LLMs), such as OpenAI's GPT-3.5, GPT-4, and GPT-4o, have garnered early and significant enthusiasm for their potent...

Artificial Intelligence Chatbots as Sources of Implant Dentistry Information for the Public: Validity and Reliability Assessment.

This study assessed the reliability and validity of responses from three chatbot systems-OpenAI's GPT-3.5, Gemini, and Copilot-concerning frequently a...

The impact of artificial intelligence usage on employee moonlighting intention: A moderated mediation model.

BackgroundAlthough occupational change is becoming commonplace for contemporary employees, it remains understudied from the theoretical perspective. W...