Single nucleotide variants (SNVs) can exert substantial and extremely variable impacts on various cellular functions, making accurate predictions of their consequences challenging, albeit crucial especially in clinical settings such as in oncology. L...
BACKGROUND: Assessing dietary phenylalanine (Phe) tolerance is crucial for managing hyperphenylalaninemia (HPA) in children. However, traditionally, adjusting the diet requires significant time from clinicians and parents. This study aims to investig...
BACKGROUND: The pretherapeutic differentiation of subtypes of primary intracranial germ cell tumours (iGCTs), including germinomas (GEs) and nongerminomatous germ cell tumours (NGGCTs), is essential for clinical practice because of distinct treatment...
. Approximately 57% of non-small cell lung cancer (NSCLC) patients face a 20% risk of brain metastases (BMs). The delivery of drugs to the central nervous system is challenging because of the blood-brain barrier, leading to a relatively poor prognosi...
BACKGROUND: Prediction-based strategies for physiologic deterioration offer the potential for earlier clinical interventions that improve patient outcomes. Current strategies are limited because they operate on inconsistent definitions of deteriorati...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 11, 2024
Decoding natural language from noninvasive brain signals has been an exciting topic with the potential to expand the applications of brain-computer interface (BCI) systems. However, current methods face limitations in decoding sentences from electroe...
AIMS: The aim of our study was to formulate and validate a prediction model using machine learning algorithms to forecast the risk of pressure injuries (PIs) in children undergoing living donor liver transplantation (LDLT).
Journal of imaging informatics in medicine
Sep 10, 2024
This study aimed to identify sex-specific imaging biomarkers for Parkinson's disease (PD) based on multiple MRI morphological features by using machine learning methods. Participants were categorized into female and male subgroups, and various struct...
RATIONALE AND OBJECTIVES: Isocitrate dehydrogenase 1 (IDH1) is a potential therapeutic target across various tumor types. Here, we aimed to devise a radiomic model capable of predicting the IDH1 expression levels in patients with head and neck squamo...
RATIONALE AND OBJECTIVES: Current radiomics research primarily focuses on intratumoral regions and fixed peritumoral areas, lacking optimization for accurate Ki-67 prediction. This study aimed to develop machine learning (ML) models to analyze radiom...
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