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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...

Federated nnU-Net for privacy-preserving medical image segmentation.

Scientific reports
The nnU-Net framework has played a crucial role in medical image segmentation and has become the gold standard in multitudes of applications targeting different diseases, organs, and modalities. However, so far it has been used primarily in a central...

Explainable artificial intelligence for predictive modeling of student stress in higher education.

Scientific reports
Student stress in higher education remains a pervasive problem, yet many institutions lack affordable, scalable, and interpretable tools for its detection and management. Existing methods frequently depend on costly physiological sensors and opaque m...

Deep learning algorithm for predicting rapid progression of abdominal aortic aneurysm by integrating CT images and clinical features.

Scientific reports
Abdominal aortic aneurysm (AAA) progression carries a significant rupture risk, demanding accurate prediction models beyond traditional methods that rely on limited clinical parameters and often overlook complex factor interplay. We aimed to enhance ...

AI-powered spatial cell phenomics enhances risk stratification in non-small cell lung cancer.

Nature communications
Risk stratification remains a critical challenge in non-small cell lung cancer patients for optimal therapy selection. In this study, we develop an artificial intelligence-powered spatial cellomics approach that combines histology, multiplex immunofl...

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...

Quality Assessment of Large Language Model-Generated Medical Dialogue for Clinical Vignettes: Evaluation Study.

JMIR formative research
BACKGROUND: Traditional clinical vignettes, though widely used in medical education, often focus on prototypical presentations; require substantial time and effort to develop; and fail to represent patient diversity, the complexity of clinical condit...

Predicting Postoperative Stress Urinary Incontinence After Prolapse Surgery via Machine Learning and Regression Models: Development and Validation Study.

JMIR medical informatics
BACKGROUND: Pelvic organ prolapse (POP) and stress urinary incontinence (SUI) often concurrently exist. The incontinence in some patients with POP resolves after POP surgery, but it persists in others. Some patients without SUI before surgery may dev...

Evaluating the Clinical Effectiveness and Patient Experience of a Large Language Model-Based Digital Tool for Home-Based Blood Pressure Management: Mixed Methods Study.

JMIR mHealth and uHealth
BACKGROUND: Hypertension, one of the most common cardiovascular conditions worldwide, necessitates comprehensive management due to its association with multiple health risks. Effective control often involves lifestyle changes and continuous monitorin...