AIMC Topic: Risk Assessment
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A machine learning model for predicting acute respiratory distress syndrome risk in patients with sepsis using circulating immune cell parameters: a retrospective study.
BMC infectious diseases
Apr 21, 2025
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a severe complication associated with a high mortality rate in patients with sepsis. Early identification of patients with sepsis at high risk of developing ARDS is crucial for timely interven...
Artificial intelligence prediction model for readmission after DIEP flap breast reconstruction based on NSQIP data.
Journal of plastic, reconstructive & aesthetic surgery : JPRAS
Apr 20, 2025
BACKGROUND: Readmissions following deep inferior epigastric perforator (DIEP) flap breast reconstruction represent a significant healthcare burden, yet current risk prediction methods lack precision in identifying high-risk patients. We developed a m...
Computational modelling for risk assessment of neurological disorder in diabetes using Hodgkin-Huxley model.
Computer methods and programs in biomedicine
Apr 20, 2025
BACKGROUND: Diabetes mellitus, characterized by chronic glucose dysregulation, significantly increases the risk of neurological disorders such as cognitive decline, seizures, and Alzheimer's disease. As neurons depend on glucose for energy, fluctuati...
Artificial intelligence to predict cancer risk, are we there yet? A comprehensive review across cancer types.
European journal of cancer (Oxford, England : 1990)
Apr 20, 2025
Cancer remains the second leading cause of death worldwide, representing a substantial challenge to global health. Although traditional risk prediction models have played a crucial role in epidemiology of several cancer types, they have limitations e...
Identification and validation of a novel machine learning model for predicting severe pelvic endometriosis: A retrospective study.
Scientific reports
Apr 19, 2025
This study aimed to explore potential risk factors for severe endometriosis and to develop a model to predict the risk of severe endometriosis. A total of 308 patients with endometriosis were analyzed. Least absolute shrinkage and selection operator ...
Artificial neural network model enhancing the accuracy of clinical evaluation for high-risk population of lymph node metastasis in non-intestinal type early gastric cancer: a multicenter real-world study in China.
International journal of surgery (London, England)
Apr 18, 2025
BACKGROUND: Recent years have witnessed a proliferation of studies aimed at developing clinical models capable of predicting lymph node metastasis (LNM) in early gastric cancer (EGC), yet tools for prediction grounded in the Lauren classification rem...
Optimizing Nutritional Care with Machine Learning: Identifying Sarcopenia Risk Through Body Composition Parameters in Cancer Patients-Insights from the NUTritional and Sarcopenia RIsk SCREENing Project (NUTRISCREEN).
Nutrients
Apr 18, 2025
: Cancer and related treatments can impair body composition (BC), increasing the risk of malnutrition and sarcopenia, poor prognosis, and Health-Related Quality of Life (HRQoL). To enhance BC parameter interpretation through Bioelectrical Impedance A...
AI-driven cybersecurity framework for software development based on the ANN-ISM paradigm.
Scientific reports
Apr 18, 2025
With the increasing reliance on software applications, cybersecurity threats have become a critical concern for developers and organizations. The answer to this vulnerability is AI systems, which help us adapt a little better, as traditional measures...
Daily Automated Prediction of Delirium Risk in Hospitalized Patients: Model Development and Validation.
JMIR medical informatics
Apr 18, 2025
BACKGROUND: Delirium is common in hospitalized patients and is correlated with increased morbidity and mortality. Despite this, delirium is underdiagnosed, and many institutions do not have sufficient resources to consistently apply effective screeni...
Assessing the association of multi-environmental chemical exposures on metabolic syndrome: A machine learning approach.
Environment international
Apr 17, 2025
Metabolic syndrome (MetS) is a major global public health concern due to its rising prevalence and association with increased risks of cardiovascular disease and type 2 diabetes. Emerging evidence suggests that environmental chemical exposures may pl...
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