AIMC Topic: Adult

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Prediction of spontaneous preterm birth using supervised machine learning on metabolomic data: A case-cohort study.

BJOG : an international journal of obstetrics and gynaecology
OBJECTIVES: To identify and internally validate metabolites predictive of spontaneous preterm birth (sPTB) using multiple machine learning methods and sequential maternal serum samples, and to predict spontaneous early term birth (sETB) using these m...

Machine Learning-Based MRI Radiogenomics for Evaluation of Response to Induction Chemotherapy in Head and Neck Squamous Cell Carcinoma.

Academic radiology
RATIONALE AND OBJECTIVES: To develop and validate a radiogenomics model integrating clinical data, radiomics-based machine learning (RBML) classifiers, and transcriptomics data for predicting the response to induction chemotherapy (IC) in patients wi...

Ultra-High-Resolution T2-Weighted PROPELLER MRI of the Rectum With Deep Learning Reconstruction: Assessment of Image Quality and Diagnostic Performance.

Investigative radiology
OBJECTIVE: The aim of this study was to evaluate the impact of ultra-high-resolution acquisition and deep learning reconstruction (DLR) on the image quality and diagnostic performance of T2-weighted periodically rotated overlapping parallel lines wit...

Staff's Attitudes towards the Use of Mobile Telepresence Robots in Long-Term Care Homes in Canada.

Canadian journal on aging = La revue canadienne du vieillissement
This cross-sectional study investigated staff's attitudes towards the use of mobile telepresence robots in long-term care (LTC) homes in western Canada. We drew on a Health Technology Assessment Core Model 3.0 to design a survey examining attitudes t...

Should All Pancreatic Cystic Lesions with Worrisome or High-Risk Features Be Resected? A Clinical and Radiological Machine Learning Model May Help to Answer.

Academic radiology
RATIONALE AND OBJECTIVES: According to current guidelines, pancreatic cystic lesions (PCLs) with worrisome or high-risk features may have overtreatment. The purpose of this study was to build a clinical and radiological based machine-learning (ML) mo...

Differentiation Between Glioblastoma and Metastatic Disease on Conventional MRI Imaging Using 3D-Convolutional Neural Networks: Model Development and Validation.

Academic radiology
RATIONALE AND OBJECTIVES: Imaging-based differentiation between glioblastoma (GB) and brain metastases (BM) remains challenging. Our aim was to evaluate the performance of 3D-convolutional neural networks (CNN) to address this binary classification p...

Students' Foreign Language Learning Adaptability and Mental Health Supported by Artificial Intelligence.

Journal of autism and developmental disorders
The rapid development of social reform and the economy has brought great challenges to the mental health of college students. However, there are few studies on the impact of these psychological problems on college students' English learning. As a spe...