Primary Care

Patients' Attitudes and Beliefs Toward Artificial Intelligence Use in Cancer Care: Cross-Sectional Survey Study.

BACKGROUND: Artificial intelligence (AI) is being rapidly integrated into oncologic care, yet little is known about how patients perceive these applications. Understanding patient perceptions is critical to ensuring AI applications align with their needs and preferences. OBJECTIVE: This study aimed to evaluate oncology patients' attitudes and beliefs on the use of AI across clinical touchpoints in...

Applying biotechnology to overcome cancer drug resistance and improve public health outcomes.

This review examines how biotechnology advances (CRISPR/Cas9, next-generation targeted therapies, nanotechnology-based drug delivery, and immunotherapies) can be applied to address cancer drug resistance worldwide. It also considers the economic burden of resistance, inequities in access to biotechnology solutions, and ethical concerns surrounding rapid innovation, particularly in low-resource set...

Interpretable machine-learning risk prediction of unplanned extubation among cancer patients with peripherally inserted central catheters.

Unplanned extubation of peripherally inserted central catheters (PICC-UE) in patients with cancer has been linked to factors including women, diabetes...

Development and interpretation of a dual-energy CT-based deep learning radiomics model for predicting new cerebral ischemic lesions after carotid artery stenting: a multicenter study.

OBJECTIVES: Early recognition of individuals at elevated risk for new ipsilateral ischemic lesions (NIILs) after carotid artery stenting (CAS) is vita...

Construction of a depression risk prediction model for hepatitis B patients based on machine learning strategy.

BACKGROUND: Hepatitis B (HBV) is a chronic viral infection that can lead to cirrhosis, liver failure, and liver cancer, and has a profound impact on t...

Artificial intelligence approaches for non-invasive diabetes prediction using ECG signals: A systematic review.

Diabetes is a major global health challenge, with many individuals remaining undiagnosed due to the limitations of traditional screening methods. Arti...

Screening, risk assessment, and rapid detection of mycotoxins in edible herbs based on UPLC-MS/MS and FT-NIR.

Mycotoxin contamination in edible herbs poses substantial health risks and economic losses due to its accumulation. This study employed a modified QuE...

Validation and longitudinal trajectory analysis of an AI-based ECG model for aortic stenosis: from community screening to pre-TAVR risk stratification.

AIMS: Early aortic stenosis (AS) detection remains challenging, with many patients presenting late when left ventricular dysfunction may be irreversib...

Machine learning-based prediction of CAC-defined cardiovascular risk using routine health examination data: a retrospective cross-sectional study in a Taiwanese population.

BACKGROUND: Early identification of individuals at elevated cardiovascular risk using routine health examination data is essential for preventive card...

Prediction of Fontan failure and correlates of Fontan-associated liver disease severity using machine learning and radiomic features from multi-parametric abdominal MRI.

BACKGROUND: Fontan-associated liver disease (FALD) is associated with morbidity and mortality in patients with palliated single ventricle congenital h...

Association and Agreement of Contact-Based Smartphone Photoplethysmography Compared With Electrocardiography: Protocol for a Systematic Review and Meta-Analysis.

BACKGROUND: Mobile health (mHealth), leveraging mobile devices for health measurement and promotion, is rapidly growing. Smartphone cameras can perfor...

AI based sagittal spinal posture assessment for adolescent screening in low resource school settings.

Adolescent spinal postural deviations are rising across Southeast Asia, driven by prolonged screen exposure and limited access to clinical screening i...

Integrating body composition analysis and machine learning for non-invasive identification of metabolic dysfunction-associated fatty liver disease: a large-scale health examination-based study.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a highly prevalent liver condition closely linked to obesity, insulin resistance, and ...

Prediction of recurrent ischemic stroke using machine learning from real-world data.

BACKGROUND: Recurrent ischemic stroke (RIS) is a significant challenge in Malaysia, affecting approximately 33% of patients. However, studies using ar...

AI Agent for Delirium Screening among Patients in Oncology and Cardiac Intensive Care Units: A Proof-of-Concept Study.

AIM: To develop and evaluate an autonomous artificial intelligence (AI) agent to support nurse-led delirium screening and guideline-concordant prevent...

An enhanced diabetes prediction using an improved hybrid deep learning algorithm with mountain gazelle optimizer.

Diabetes is one of the global health challenges and requires early detection and an accurate diagnosis for the prevention of serious complications. Tr...

Machine learning-assisted screening of small-molecule drugs for suppressing protein aggregation and ROS generation based on ECL and CV dual-mode signals amplified by DNA.

Screening of small-molecule drugs to suppress both protein aggregation and reactive oxygen species (ROS) generation is critical for developing therapi...

RenoTrue: A diabetes-specific machine learning model to estimate glomerular filtration rate for people with diabetes.

BACKGROUND: Existing methods for estimating GFR in people with diabetes have shown inaccuracies when compared to mGFR measurements. We developed and v...

Ethical and Bioethical Issues in Physical Therapy: A Systematic Scoping Review.

IMPORTANCE: Ethical and bioethical issues are central to the identity and practice of physical therapy. A comprehensive overview of how these issues a...

Developing a Multimodal Screening Algorithm for Mild Cognitive Impairment and Early Dementia in Home Health Care: Protocol for a Cross-Sectional Case-Control Study Using Speech Analysis, Large Language Models, and Electronic Health Records.

BACKGROUND: Mild cognitive impairment and early dementia (MCI-ED) are frequently unrecognized in routine care, particularly in home health care (HHC),...