AIMC Topic: Adult

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Acceptability of a Conversational Agent-Led Digital Program for Anxiety: Mixed Methods Study of User Perspectives.

JMIR human factors
BACKGROUND: The prevalence of anxiety and depression is increasing globally, outpacing the capacity of traditional mental health services. Digital mental health interventions (DMHIs) provide a cost-effective alternative, but user engagement remains l...

The relationship between the neutrophil percentage to albumin ratio and the occurrence of prostate cancer.

PloS one
BACKGROUND: Although prior research has indicated that nutritional and inflammatory markers may play a role in prostate cancer development, the exact interplay and underlying mechanisms are not yet fully understood.

E-RespiNet: An LLM-ELECTRA driven triple-stream CNN with feature fusion for asthma classification.

PloS one
Respiratory disease diagnosis remains challenging in resource-constrained settings, where limited specialist expertise contributes to diagnostic uncertainties affecting over 300 million people worldwide. This study presents E-RespiNet, a novel multi-...

Robot or human? Manoeuvring switching intention after robot service failure.

PloS one
This study attempts to scrutinise tourists' switching intentions towards human service after a robot service failure, with the zone of tolerance and trust on stance in technology as moderators. The study adopts the unified theory of acceptance and us...

Interpretable machine learning model for predicting low birth weight in singleton pregnancies: a retrospective cohort study.

BMC pregnancy and childbirth
BACKGROUND: Low birth weight (LBW), defined as a newborn weighing less than 2500 g, is an increasingly significant public health concern. Exploring the risk and protective factors for LBW is getting more and more important. This study aimed to utiliz...

Enhanced stratification of male pattern hair loss using AI through novel loss region ratio analysis.

Scientific reports
Male pattern hair loss (MPHL) is a common dermatological condition with significant psychological and clinical impacts. Traditional grading systems, such as the Norwood-Hamilton and Basic and Specific (BASP) classifications, rely on subjective assess...

Machine learning prediction of overall survival in patients with cT1b renal cell carcinoma after surgical resection using the SEER database.

Scientific reports
Accurate survival prediction is essential for guiding follow-up strategies in patients with cT1b renal cell carcinoma (RCC). Traditional AJCC TNM staging systems provide limited prognostic accuracy. Data from the SEER database were used, which includ...

A cross sectional feasibility study to evaluate the usability and efficacy of Swaasa AI platform for rapid respiratory health assessment.

Scientific reports
Analysing cough sounds is vital in pulmonary medicine. Recently, AI tools are being trained to analyse the acoustic signals of cough sounds so that more cases can be quickly tested, thereby reducing the patient load on primary healthcare systems. In ...

A personalized federated learning-based glucose prediction algorithm for high-risk glycemic excursion regions in type 1 diabetes.

Scientific reports
Continuous glucose monitoring (CGM) devices allow real-time glucose readings leading to improved glycemic control. However, glucose predictions in the lower (hypoglycemia) and higher (hyperglycemia) extremes, referred as glycemic excursions, remain c...

Development and validation of a clinical wearable deep learning based continuous inhospital deterioration prediction model.

Nature communications
Standard episodic patient monitoring of vital signs on the medical-surgical wards can potentially miss changes in health status and delay recognition of risk. To reduce these delays, we develop a clinical wearable-based deep learning model, using 9 i...