AIMC Topic: Machine Learning

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Prediction of immune checkpoint inhibition with immune oncology-related gene expression in gastrointestinal cancer using a machine learning classifier.

Journal for immunotherapy of cancer
Immune checkpoint inhibitors (ICIs) have revolutionized the therapeutic landscape of gastrointestinal cancer. However, biomarkers correlated with the efficacy of ICIs in gastrointestinal cancer are still lacking. In this study, we performed 395-plex ...

Comparison of data analytics strategies in computer vision systems to predict pig body composition traits from 3D images.

Journal of animal science
Computer vision systems (CVS) have been shown to be a powerful tool for the measurement of live pig body weight (BW) with no animal stress. With advances in precision farming, it is now possible to evaluate the growth performance of individual pigs m...

Machine learning for classification and prediction of brain diseases: recent advances and upcoming challenges.

Current opinion in neurology
PURPOSE OF REVIEW: Machine learning is an artificial intelligence technique that allows computers to perform a task without being explicitly programmed. Machine learning can be used to assist diagnosis and prognosis of brain disorders. Although the e...

Fold-stratified cross-validation for unbiased and privacy-preserving federated learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We introduce fold-stratified cross-validation, a validation methodology that is compatible with privacy-preserving federated learning and that prevents data leakage caused by duplicates of electronic health records (EHRs).

Machine learning methods in organ transplantation.

Current opinion in organ transplantation
PURPOSE OF REVIEW: Machine learning techniques play an important role in organ transplantation. Analysing the main tasks for which they are being applied, together with the advantages and disadvantages of their use, can be of crucial interest for cli...

Machine Learning Prognostic Models for Gastrointestinal Bleeding Using Electronic Health Record Data.

The American journal of gastroenterology
Risk assessment tools for patients with gastrointestinal bleeding may be used for determining level of care and informing management decisions. Development of models that use data from electronic health records is an important step for future deploym...

Applying Artificial Intelligence to Mitigate Effects of Patient Motion or Other Complicating Factors on Image Quality.

Topics in magnetic resonance imaging : TMRI
Artificial intelligence, particularly deep learning, offers several possibilities to improve the quality or speed of image acquisition in magnetic resonance imaging (MRI). In this article, we briefly review basic machine learning concepts and discuss...

Machine-learning algorithms for predicting results in liver transplantation: the problem of donor-recipient matching.

Current opinion in organ transplantation
PURPOSE OF REVIEW: Classifiers based on artificial intelligence can be useful to solve decision problems related to the inclusion or removal of possible liver transplant candidates, and assisting in the heterogeneous field of donor-recipient (D-R) ma...

Artificial intelligence in transplantation (machine-learning classifiers and transplant oncology).

Current opinion in organ transplantation
PURPOSE OF REVIEW: To highlight recent efforts in the development and implementation of machine learning in transplant oncology - a field that uses liver transplantation for the treatment of hepatobiliary malignancies - and particularly in hepatocell...