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Multiple instance learning using pathology foundation models effectively predicts kidney disease diagnosis and clinical classification.

Scientific reports
Recently developed pathology foundation models, pretrained on large-scale pathology datasets, have demonstrated excellent performance in various downstream tasks. This study evaluated the utility of pathology foundation models combined with multiple ...

Hierarchical random forest model, inflammation and oxidative stress as predictors of the atherogenic index of plasma and diabetes progression.

Scientific reports
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease that increases the risk of cardiovascular complications. The atherogenic index of plasma (AIP) is a risk marker for T2DM and cardiovascular disease on the basis of lipid profiles. T2DM an...

Decoding trust in large language models for healthcare in Saudi Arabia.

Scientific reports
This study investigates the factors influencing user trust and decision-making when using Artificial Intelligence (AI) systems, specifically focusing on ChatGPT in the healthcare domain within the Saudi context. As AI-powered conversational agents ar...

Deep phenotyping of patient lived experience in functional bowel disorders using machine learning.

Scientific reports
Contemporary clinical management relies on a diagnostic label as the primary guide to treatment. However, individual patients' lived experiences vary more widely than standard diagnostic categories reflect. This is especially true for functional bowe...

Preoperative prediction of lymph node metastasis risk in papillary thyroid carcinoma based on multiple model comparisons.

Scientific reports
The clinical necessity of lymph node dissection in papillary thyroid carcinoma (PTC) surgery remains contentious. This study compared four logistic regression (LR) models (with distinct feature selection strategies) and four machine learning (ML) mod...

Exploring parameter optimisation in machine learning algorithms for locomotor task discrimination using wearable sensors.

Scientific reports
The accurate identification of locomotion states from wearable sensor data using machine learning relies heavily on carefully selecting algorithm parameters, which remains a challenging task. This study systematically optimised key parameters-includi...

Students' perceptions of AI mental health chatbots: an exploratory qualitative study at Sultan Qaboos University.

BMJ open
OBJECTIVES: The aim of this study is to explore the perceptions, attitudes and previous experiences of Sultan Qaboos University (SQU) students towards artificial intelligence (AI) mental health chatbots.

Artificial Intelligence Driven Diagnosis and Prognosis Comparison of ChatGPT-4o and DeepSeek-R1 in HIV Negative Talaromycosis.

Mycopathologia
This study evaluates and compares the diagnostic and prognostic capabilities of ChatGPT-4o and DeepSeek-R1 in 56 HIV-negative talaromycosis cases. Clinical case fragments were de-identified and submitted to both models, with diagnostic accuracy and p...

Source-free domain adaptation for SSVEP-based brain-computer interfaces.

Journal of neural engineering
Steady-state visually evoked potential-based Brain-computer interface (BCI) spellers assist individuals experiencing speech difficulties by enabling them to communicate at a fast rate. However, achieving a high information transfer rate (ITR) in most...

Impact of the oxidative balance score on cardiovascular-kidney-metabolic syndrome: A cross-sectional study with machine learning prediction.

PloS one
BACKGROUND AND AIM: The antioxidant diet and lifestyle are widely believed to prevent and even treat various diseases; however, their applicability to cardiovascular-kidney-metabolic (CKM) syndrome remains unknown. In this study, the correlation betw...