Surveys

Use of artificial intelligence in transfusion medicine practice, education and research: A mixed methodology study.

BACKGROUND AND OBJECTIVES: The artificial intelligence (AI) field holds significant promise to revolutionize healthcare, including transfusion medicine (TM). This study explored AI use in TM, education and research among International Society of Blood Transfusion (ISBT) members. MATERIALS AND METHODS: A mixed methodology was employed. A survey was conducted June to November 2024. Eighteen particip...

Dental Students' Knowledge, Attitudes and Perceptions of Artificial Intelligence Tools to Aid in the Diagnosis of Oral Cancer and Oral Potentially Malignant Disorders.

BACKGROUND: Artificial intelligence (AI) has emerged as a promising tool in dentistry, particularly in the early detection of oral cancer (OC) and oral potentially malignant disorders (OPMDs). Data focused on European dental students and their knowledge/attitudes towards the use of AI for diagnosing OC/OPMDs are limited. METHODS: A cross-sectional online survey was conducted among final-year denta...

Integrated Deep Learning-Based Intracranial Vessel Wall Imaging with DANTE Preparation: Feasibility and Technical Performance.

PURPOSE: To evaluate the feasibility and technical performance of integrating a Delay Alternating with Nutation for Tailored Excitation (DANTE) prepar...

Predicting neoadjuvant immunotherapy efficacy with machine learning models in non-small cell lung cancer: A systematic review and meta analysis.

BACKGROUND: The response of resectable non-small cell lung cancer (NSCLC) to neoadjuvant immunotherapy is heterogeneous. Machine learning can integrat...

Psychological determinants of transport mode choice: A comprehensive dataset from Pabna Municipality, Bangladesh.

This data article introduces a detailed and structured dataset derived from a survey exploring the psychological factors that influence transport mode...

Prevalence and factors associated with suicidal ideation based on the Malaysia National Health and Morbidity Survey: A machine learning analysis.

BACKGROUND: This study estimated the prevalence of past-two-week suicidal ideation and examined its demographic, clinical, and health-related correlat...

Automating classification of treatment responses to combined targeted therapy and immunotherapy in HCC.

Tyrosine kinase inhibitor (TKI) combined with immunotherapy regimens are now widely used for treating advanced hepatocellular carcinoma (HCC), but the...

Patients Are Generally Supportive of Artificial Intelligence in Breast Imaging: A Multisite Survey of Breast Imaging Patients.

OBJECTIVE: To understand the perspective of patients undergoing breast imaging on the use of artificial intelligence (AI) in breast cancer screening. ...

Medical students' mental health, quality of life, motivation, and learning approaches before, during and after COVID-19: findings from a 4-wave repeated cross-sectional survey.

This study examined changes in mental health, quality of life, academic motivation, and learning approaches before, during, and after the COVID-19, pa...

Overview of a User-Centered, Mixed-Methods Process for Designing Interconnected and Focused Mobile Applications on Patient Care Environment (InterFACE): Augmented-Reality Decision Support System for Pediatric Resuscitation.

BACKGROUND: Pediatric cardiopulmonary resuscitation (CPR) is a highly complex and time-critical process that demands precise team coordination and str...

Real-World Use of a Mental Health AI Companion: Multiple Methods Study.

BACKGROUND: The rapid acceleration of large language models (LLMs) creates opportunities to expand the accessibility of mental health support; however...

Can Artificial Intelligence Align with Evidence? Performance of ChatGPT-4o in Knee Osteoarthritis Surgical Guidelines.

Artificial intelligence large language models (LLMs) such as ChatGPT are increasingly used in clinical settings, yet their reliability in reproducing ...

Early Risk Factor Prediction in Chronic Kidney Disease Diagnosis Using Feature Selection and Machine Learning Algorithms.

Chronic kidney disease, CKD in short, is a kind of long-term kidney illness in which rapid deterioration of kidney function is observed over a period ...

A hybrid LSTM-GRU framework for lung cancer classification using GWO-WOA algorithm for hyperparameter tuning and BPSO for feature selection.

Early identification of lung cancer using questionnaire-based data offers a low-cost, non-invasive pathway to assist clinical decision-making. However...

AI/ML-based strategies for enhancing equity, diversity, and inclusion in randomized clinical trials.

This paper introduces a conceptual framework designed to embed equity, diversity, and inclusion (EDI) across all stages of the clinical trial lifecycl...

Enhancing reliability in electrical grids: A hybrid machine learning approach for electrical faults classification.

Transmission lines are vital components of electrical grids, ensuring the efficient transfer of electricity from power plants to consumers over extens...

Brain Mechanisms of Pain Anticipation in Chronic Low Back Pain: Insights into Phenotypical Responses to Mind-Body Therapy.

Pain perception and emotional processing share common predictive mechanisms influenced by anticipation, expectation, and uncertainty. This study ident...

Enhancing dental clinical education through AI: insights into post-clinical summaries.

BACKGROUND: Artificial Intelligence (AI) is increasingly being introduced into clinical education, including dentistry, as a supplement to traditional...

Early Maturation of Heart Rate Variability in Very Preterm Infants Depends on Neonatal Factors and Is Associated With Neurodevelopmental Risk.

AIM: This study investigated central autonomic network maturation deviations using a previously defined machine learning model set to estimate a funct...

Machine Learning for Predicting Venous Thromboembolism After Joint Arthroplasty: Systematic Review of Clinical Applicability and Model Performance.

BACKGROUND: There is increasing research on machine learning in predicting venous thromboembolism after joint arthroplasty, but the quality and clinic...