BACKGROUND: Accurate prediction of pathologic complete response (pCR) following neoadjuvant immunotherapy combined with chemotherapy (nICT) is crucial for tailoring patient care in esophageal squamous cell carcinoma (ESCC). This study aimed to develo...
BACKGROUND: Early childhood caries (ECC) is a major oral health problem among preschool children that can significantly influence children's quality of life. Machine learning can accurately predict the treatment outcome but its use in ECC management ...
OBJECTIVES: Novel non-invasive machine learning algorithms may improve accuracy and reduce the need for biopsy when diagnosing idiopathic pulmonary fibrosis (IPF). We conducted a cost-effectiveness analysis of diagnostic strategies for IPF.
BACKGROUND: Surrogate insulin resistance (IR) indices are simpler and more practical alternatives to insulin-based IR indicators for clinical use. This study explored the association between surrogate IR indices, including triglyceride-glucose index ...
BACKGROUND: Artificial intelligence (AI) has shown immense potential in the field of medicine, but its actual effectiveness and safety still need to be validated through clinical trials. Currently, the research themes, methodologies, and development ...
Physicians evaluate a patient's respiratory health during a physical examination by visual assessment of the work of breathing (WoB) to determine respiratory stability, and by detecting abnormal lung sounds via lung auscultation using a stethoscope t...
Machine learning can be applied to identify key genes associated with osteoarthritis (OA). This study aimed to explore the differential expression of necroptosis-related genes (NRGs) during the progression of OA, identify key gene modules strongly li...
In this study, the biological activities of the extracts obtained under optimum extraction conditions of the kernel part of Juglans regia L. were determined. Two different methods, Response Surface Method (RSM) and Artificial Neural Network-Genetic A...
This study presents a systematic review (SR) and meta-analysis (MA) on the use of machine learning (ML) methods for detecting online grooming, a form of manipulation and child sexual abuse. The SR identified 33 studies from IEEE, Web of Science, Scop...
Deception detection is crucial in domains like national security, privacy, judiciary, and courtroom trials. Differentiating truth from lies is inherently challenging due to many complex, diversified behavioural, physiological and cognitive aspects. T...
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