AIMC Topic: Area Under Curve

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Ensemble learning based on overlapping clusters of subjects to predict microsleep states from EEG.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Microsleeps are brief and involuntary instances of complete loss of sleep-related consciousness. We present a novel approach of creating overlapping clusters of subjects and training of an ensemble classifier to enhance the prediction of microsleep s...

Patch-level Tumor Classification in Digital Histopathology Images with Domain Adapted Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Tumor histopathology is a crucial step in cancer diagnosis which involves visual inspection of imaging data to detect the presence of tumor cells among healthy tissues. This manual process can be time-consuming, error-prone, and influenced by the exp...

Pharmacokinetic Therapeutic Drug Monitoring of Advagraf in More Than 500 Adult Renal Transplant Patients, Using an Expert System Online.

Therapeutic drug monitoring
BACKGROUND: Immunosuppressant Bayesian dose adjustment (ISBA) is an online expert system, routinely used by approximately 140 transplantation centers in the world for the dose adjustment of immunosuppressive drugs in transplant patients. This system ...

Predicting Corticosteroid-Free Biologic Remission with Vedolizumab in Crohn's Disease.

Inflammatory bowel diseases
BACKGROUND AND AIMS: Vedolizumab (VDZ) is effective for Crohn's disease (CD) but costly and is slow to produce remission. Early knowledge of whether vedolizumab is likely to succeed is valuable for physicians, patients, and insurers.

Predictive Modeling of Hamstring Strain Injuries in Elite Australian Footballers.

Medicine and science in sports and exercise
PURPOSE: Three of the most commonly identified hamstring strain injury (HSI) risk factors are age, previous HSI, and low levels of eccentric hamstring strength. However, no study has investigated the ability of these risk factors to predict the incid...

DDR: efficient computational method to predict drug-target interactions using graph mining and machine learning approaches.

Bioinformatics (Oxford, England)
MOTIVATION: Finding computationally drug-target interactions (DTIs) is a convenient strategy to identify new DTIs at low cost with reasonable accuracy. However, the current DTI prediction methods suffer the high false positive prediction rate.

Validation of artificial neural networks as a methodology for donor-recipient matching for liver transplantation.

Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society
In 2014, we reported a model for donor-recipient (D-R) matching in liver transplantation (LT) based on artificial neural networks (ANNs) from a Spanish multicenter study (Model for Allocation of Donor and Recipient in EspaƱa [MADR-E]). The aim is to ...

Predicting Hospitalization and Outpatient Corticosteroid Use in Inflammatory Bowel Disease Patients Using Machine Learning.

Inflammatory bowel diseases
BACKGROUND: Inflammatory bowel disease (IBD) is a chronic disease characterized by unpredictable episodes of flares and periods of remission. Tools that accurately predict disease course would substantially aid therapeutic decision-making. This study...