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Predicting therapeutic clinical trial enrollment for adult patients with low- and high-grade glioma using supervised machine learning.
Science advances
Jun 4, 2025
Therapeutic clinical trial enrollment does not match glioma incidence across demographics. Traditional statistical methods have identified independent predictors of trial enrollment; however, our understanding of the interactions between these factor...
Prediction of depression risk in middle-aged and elderly Cardiovascular-Kidney-Metabolic syndrome patients by social and environmental determinants of health: an interpretable machine learning approach using longitudinal data from China.
Journal of health, population, and nutrition
Jun 4, 2025
BACKGROUND: Cardiovascular-Kidney-Metabolic (CKM) syndrome is a systemic disease characterized by pathophysiological interactions between the cardiovascular system, chronic kidney disease, and metabolic risk factors. In China, the prevalence of CKM i...
Machine learning-based prediction of respiratory depression during sedation for liposuction.
Scientific reports
Jun 4, 2025
Procedural sedation is often performed by non-anesthesiologists in various settings and can lead to respiratory depression. A tool that enables early detection of respiratory compromise could not only enhance patient safety during procedural sedation...
UNIK (Urologic Non-Neoplastic Investigation of Kidneys): a machine learning approach to decode benign lesion.
World journal of urology
Jun 4, 2025
PURPOSE: Predicting the likelihood of benign neoplasia in patients with suspected renal cell carcinoma (RCC) is a cornerstone of presurgical planning. We sought to create and validate U.N.I.K., a machine learning (ML) model capable of predicting beni...
Machine learning models for predicting severe acute kidney injury in patients with sepsis-induced myocardial injury.
Scientific reports
Jun 4, 2025
Severe acute kidney injury (sAKI) is a prevalent and serious complication among patients with sepsis-induced myocardial injury (SIMI). Prompt and early prediction of sAKI has an important role in timely intervention, ultimately improving the patients...
Development of a machine learning-based model to predict urethral recurrence following radical cystectomy: a multicentre retrospective study and updated meta-analysis.
Scientific reports
Jun 4, 2025
Urethral recurrence (UR) following radical cystectomy for bladder cancer represents an aggressive disease failure with typically poor survival outcomes. Our study aimed to assess the predictive risk factors for UR, to develop and validate an easy-to-...
Determining the Requirements of Vulnerable Groups for Health Counseling and Optimizing the Evaluation of Health Consultations: Mixed Methods Study With the Use of AI.
JMIR formative research
Jun 4, 2025
BACKGROUND: Evaluating health counseling services is crucial for ensuring their quality and effectiveness. However, this process is hampered by challenges such as language barriers and limited awareness of their needs and concerns.
Mortality Prediction Performance Under Geographical, Temporal, and COVID-19 Pandemic Dataset Shift: External Validation of the Global Open-Source Severity of Illness Score Model.
Critical care explorations
Jun 4, 2025
BACKGROUND: Risk-prediction models are widely used for quality of care evaluations, resource management, and patient stratification in research. While established models have long been used for risk prediction, healthcare has evolved significantly, a...
Dynamically weighted graph neural network for detection of early mild cognitive impairment.
PloS one
Jun 4, 2025
Alzheimer's disease (AD) is a prevalent neurodegenerative disease that primarily affects the elderly population. The early detection of mild cognitive impairment (MCI) holds significant clinical importance for prompt intervention and treatment of AD....
Super-resolution sodium MRI of human gliomas at 3T using physics-based generative artificial intelligence.
Journal of neuro-oncology
Jun 3, 2025
PURPOSE: Sodium neuroimaging provides unique insights into the cellular and metabolic properties of brain tumors. However, at 3T, sodium neuroimaging MRI's low signal-to-noise ratio (SNR) and resolution discourages routine clinical use. We evaluated ...
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