AIMC Topic: Humans

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Integrating the STOP-BANG Score and Clinical Data to Predict Cardiovascular Events After Infarction: A Machine Learning Study.

Chest
BACKGROUND: OSA conveys worse clinical outcomes in patients with coronary artery disease. The STOP-BANG score is a simple tool that evaluates the risk of OSA and can be added to the large number of clinical variables and scores that are obtained duri...

Comparison of deep learning models for natural language processing-based classification of non-English head CT reports.

Neuroradiology
PURPOSE: Natural language processing (NLP) can be used for automatic flagging of radiology reports. We assessed deep learning models for classifying non-English head CT reports.

Machine-learning models for depression and anxiety in individuals with immune-mediated inflammatory disease.

Journal of psychosomatic research
OBJECTIVE: Individuals with immune-mediated inflammatory disease (IMID) have a higher prevalence of psychiatric disorders than the general population. We utilized machine-learning to identify patient-reported outcome measures (PROMs) that accurately ...

A cross-modal 3D deep learning for accurate lymph node metastasis prediction in clinical stage T1 lung adenocarcinoma.

Lung cancer (Amsterdam, Netherlands)
OBJECTIVES: The evaluation of lymph node (LN) status by radiologists based on preoperative computed tomography (CT) lacks high precision for early lung cancer patients; erroneous evaluations result in inappropriate therapeutic plans and increase the ...

Finding warning markers: Leveraging natural language processing and machine learning technologies to detect risk of school violence.

International journal of medical informatics
INTRODUCTION: School violence has a far-reaching effect, impacting the entire school population including staff, students and their families. Among youth attending the most violent schools, studies have reported higher dropout rates, poor school atte...

Harmonized representation learning on dynamic EHR graphs.

Journal of biomedical informatics
With the rise of deep learning, several recent studies on deep learning-based methods for electronic health records (EHR) successfully address real-world clinical challenges by utilizing effective representations of medical entities. However, existin...

Clinically Feasible and Accurate View Classification of Echocardiographic Images Using Deep Learning.

Biomolecules
A proper echocardiographic study requires several video clips recorded from different acquisition angles for observation of the complex cardiac anatomy. However, these video clips are not necessarily labeled in a database. Identification of the acqui...

Preoperative assessment of lymph node metastasis in Colon Cancer patients using machine learning: a pilot study.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Preoperative detection of lymph node (LN) metastasis is critical for planning treatments in colon cancer (CC). The clinical diagnostic criteria based on the size of the LNs are not sensitive to determine metastasis using CT images. In thi...

Comparison of statistical and machine learning models for healthcare cost data: a simulation study motivated by Oncology Care Model (OCM) data.

BMC health services research
BACKGROUND: The Oncology Care Model (OCM) was developed as a payment model to encourage participating practices to provide better-quality care for cancer patients at a lower cost. The risk-adjustment model used in OCM is a Gamma generalized linear mo...