AIMC Topic: Cohort Studies
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Predicting recurrent gestational diabetes mellitus using artificial intelligence models: a retrospective cohort study.
Archives of gynecology and obstetrics
Jul 30, 2024
BACKGROUND: We aimed to develop novel artificial intelligence (AI) models based on early pregnancy features to forecast the likelihood of recurrent gestational diabetes mellitus (GDM) before 14 weeks of gestation in subsequent pregnancies.
Identification of profiles associated with conversions between the Alzheimer's disease stages, using a machine learning approach.
Alzheimer's research & therapy
Jul 26, 2024
BACKGROUND: The identification of factors involved in the conversion across the different Alzheimer's disease (AD) stages is crucial to prevent or slow the disease progression. We aimed to assess the factors and their combination associated with the ...
A multi-Task Learning based applicable AI model simultaneously predicts stage, histology, grade and LNM for cervical cancer before surgery.
BMC women's health
Jul 26, 2024
PURPOSE: To build an Mult-Task Learning (MTL) based Artificial Intelligence(AI) model that can simultaneously predict clinical stage, histology, grade and LNM for cervical cancer before surgery.
Development and External Validation of a Machine Learning-based Fall Prediction Model for Nursing Home Residents: A Prospective Cohort Study.
Journal of the American Medical Directors Association
Jul 24, 2024
OBJECTIVES: To develop and externally validate a machine learning-based fall prediction model for ambulatory nursing home residents. The focus is on predicting fall occurrences within 6 months after baseline assessment through a binary classification...
A stacking ensemble model for predicting the occurrence of carotid atherosclerosis.
Frontiers in endocrinology
Jul 23, 2024
BACKGROUND: Carotid atherosclerosis (CAS) is a significant risk factor for cardio-cerebrovascular events. The objective of this study is to employ stacking ensemble machine learning techniques to enhance the prediction of CAS occurrence, incorporatin...
Development and Validation of a Machine Learning COVID-19 Veteran (COVet) Deterioration Risk Score.
Critical care explorations
Jul 19, 2024
BACKGROUND AND OBJECTIVE: To develop the COVid Veteran (COVet) score for clinical deterioration in Veterans hospitalized with COVID-19 and further validate this model in both Veteran and non-Veteran samples. No such score has been derived and validat...
Prediction of prognosis in lung cancer using machine learning with inter-institutional generalizability: A multicenter cohort study (WJOG15121L: REAL-WIND).
Lung cancer (Amsterdam, Netherlands)
Jul 18, 2024
OBJECTIVES: Predicting the prognosis of lung cancer is crucial for providing optimal medical care. However, a method to accurately predict the overall prognosis in patients with stage IV lung cancer, even with the use of machine learning, has not bee...
At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods.
Scientific reports
Jul 16, 2024
By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with me...
Deriving Automated Device Metadata From Intracranial Pressure Waveforms: A Transforming Research and Clinical Knowledge in Traumatic Brain Injury ICU Physiology Cohort Analysis.
Critical care explorations
Jul 16, 2024
IMPORTANCE: Treatment for intracranial pressure (ICP) has been increasingly informed by machine learning (ML)-derived ICP waveform characteristics. There are gaps, however, in understanding how ICP monitor type may bias waveform characteristics used ...
Decoding depression: a comprehensive multi-cohort exploration of blood DNA methylation using machine learning and deep learning approaches.
Translational psychiatry
Jul 15, 2024
The causes of depression are complex, and the current diagnosis methods rely solely on psychiatric evaluations with no incorporation of laboratory biomarkers in clinical practices. We investigated the stability of blood DNA methylation depression sig...
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