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Pre-operatively predicting kidney stone recurrence: integrating radiomic features and clinical variables using machine learning.

BMC medical imaging
BACKGROUND: Radiomics and artificial intelligence have shown strong predictive capabilities in urinary stone research, particularly concerning stone composition, characteristics, and treatment outcomes. However, the association of stone radiomics and...

NeuroAgeFusionNet an ensemble deep learning framework integrating CNN, transformers, and GNN for robust brain age estimation using MRI scans.

Scientific reports
Brain age prediction based on anatomical MRI scans, as an essentially new measure in neuroimaging and aging research, provides a crucial marker for the early diagnosis of neurodegenerative diseases, cognitive health appraisal, and biological age pred...

Detect pre-cancerous tongue lesions for early oral cancer diagnosis using deep learning algorithm.

Scientific reports
Precancerous tongue lesion is a prevalent, complex, and highly perilous kind of cancer. The tumour might be in the salivary glands, tonsils, neck, cheek, and mouth. Oral Cancer (OC) is commonly identified in advanced stages due to the limited accurac...

Explainable ensemble learning for Epstein-Barr virus risk prediction in ulcerative colitis and Crohn's disease using routine biomarkers.

Scientific reports
Epstein-Barr virus (EBV) exacerbates inflammatory bowel disease (IBD) and is challenging to monitor with invasive or costly tests. We investigated whether explainable machine learning can predict EBV infection from routine clinical data in ulcerative...

Spatiotemporal multimodal emotion recognition using Temporal video sequences and pose features for child emotion classification.

Scientific reports
Developmental psychology and affective computing have placed great emphasis on identifying children's emotional cues in recent times. In this study, a novel Spatio-Temporal Multimodal Emotion Recognition Network (ST-MERN) for child emotion classifica...

Classifying schizophrenia subtypes via resting-state EEG complexity networks.

Scientific reports
Schizophrenia (SZ) is increasingly recognized as a network disorder marked by abnormal functional connectivity, yet the clinical utility of fMRI remains limited. Electroencephalography (EEG) provides a more practical alternative, though conventional ...

A machine learning model and molecular clusters of epigenetic chromatin regulators in tuberculosis based on bioinformatics and clinical samples.

Scientific reports
The role of chromatin regulators (CRs) in mediating epigenetic changes during tuberculosis (TB) infection remains poorly understood. This study aimed to determine the efficacy of CRs in diagnosing TB and characterizing its heterogeneity. GSE83456 dat...

Machine learning driven multiomics analysis identifies disulfidptosis associated molecular subtypes in ovarian cancer.

Scientific reports
Precision oncology enables molecularly guided cancer therapy through multi-omics profiling, AI-driven classification, and biomarker-targeted interventions. Disulfidptosis has emerged as a promising therapeutic target, yet no ovarian cancer classifica...

PDualNet: a deep learning framework for joint prediction of Parkinson's disease progression subtype and MDS-UPDRS scores.

Scientific reports
Parkinson's disease is one of the most common and complex neurodegenerative diseases, characterized by remarkable motor and cognitive decline. As it is a highly heterogeneous disorder, i.e., the specific symptoms, their severity, and their progressio...

Design and development of a portable multiwavelength LED-based diffuse reflectance spectroscopy tool for rapid breast cancer identification.

Scientific reports
Breast cancer is the most prevalent cancer among women worldwide, emphasizing the need for rapid and accurate diagnostic tools to improve patient outcomes and survival rates. In this study, we developed a diagnostic tool-a multispectral pen based on ...