AIMC Topic: ROC Curve

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Deep Learning/Artificial Intelligence and Blood-Based DNA Epigenomic Prediction of Cerebral Palsy.

International journal of molecular sciences
The etiology of cerebral palsy (CP) is complex and remains inadequately understood. Early detection of CP is an important clinical objective as this improves long term outcomes. We performed genome-wide DNA methylation analysis to identify epigenomic...

Prediction of response after chemoradiation for esophageal cancer using a combination of dosimetry and CT radiomics.

European radiology
PURPOSE: To investigate the treatment response prediction feasibility and accuracy of an integrated model combining computed tomography (CT) radiomic features and dosimetric parameters for patients with esophageal cancer (EC) who underwent concurrent...

An Adaptive Moment estimation method for online AUC maximization.

PloS one
Area Under the ROC Curve (AUC) is a widely used metric for measuring classification performance. It has important theoretical and academic values to develop AUC maximization algorithms. Traditional methods often apply batch learning algorithm to maxi...

mACPpred: A Support Vector Machine-Based Meta-Predictor for Identification of Anticancer Peptides.

International journal of molecular sciences
Anticancer peptides (ACPs) are promising therapeutic agents for targeting and killing cancer cells. The accurate prediction of ACPs from given peptide sequences remains as an open problem in the field of immunoinformatics. Recently, machine learning ...

Predicting childhood obesity using electronic health records and publicly available data.

PloS one
BACKGROUND: Because of the strong link between childhood obesity and adulthood obesity comorbidities, and the difficulty in decreasing body mass index (BMI) later in life, effective strategies are needed to address this condition in early childhood. ...

Toward an Expert Level of Lung Cancer Detection and Classification Using a Deep Convolutional Neural Network.

The oncologist
BACKGROUND: Computed tomography (CT) is essential for pulmonary nodule detection in diagnosing lung cancer. As deep learning algorithms have recently been regarded as a promising technique in medical fields, we attempt to integrate a well-trained dee...

Viable and necrotic tumor assessment from whole slide images of osteosarcoma using machine-learning and deep-learning models.

PloS one
Pathological estimation of tumor necrosis after chemotherapy is essential for patients with osteosarcoma. This study reports the first fully automated tool to assess viable and necrotic tumor in osteosarcoma, employing advances in histopathology digi...