AIMC Topic: Machine Learning

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Neural activity reveals interactions between episodic and semantic memory systems during retrieval.

Journal of experimental psychology. General
Whereas numerous findings support a distinction between episodic and semantic memory, it is now widely acknowledged that these two forms of memory interact during both encoding and retrieval. The precise nature of this interaction, however, remains p...

Automatic hip geometric feature extraction in DXA imaging using regional random forest.

Journal of X-ray science and technology
BACKGROUND: Hip fracture is considered one of the salient disability factors across the global population. People with hip fractures are prone to become permanently disabled or die from complications. Although currently the premier determiner, bone m...

Doctor AI.

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons

Machine Learning Approach for Predicting New Uses of Existing Drugs and Evaluation of Their Reliabilities.

Methods in molecular biology (Clifton, N.J.)
In this chapter, a new method to evaluate the reliability of predicting new uses of existing drugs was proposed. The prediction was performed with a support vector machine (SVM) using various data. Because the reliability of prediction could not be e...

A Machine-Learning-Based Drug Repurposing Approach Using Baseline Regularization.

Methods in molecular biology (Clifton, N.J.)
We present the baseline regularization model for computational drug repurposing using electronic health records (EHRs). In EHRs, drug prescriptions of various drugs are recorded throughout time for various patients. In the same time, numeric physical...

Computational Prediction of Drug-Target Interactions via Ensemble Learning.

Methods in molecular biology (Clifton, N.J.)
Therapeutic effects of drugs are mediated via interactions between them and their intended targets. As such, prediction of drug-target interactions is of great importance. Drug-target interaction prediction is especially relevant in the case of drug ...

Using Drug Expression Profiles and Machine Learning Approach for Drug Repurposing.

Methods in molecular biology (Clifton, N.J.)
The cost of new drug development has been increasing, and repurposing known medications for new indications serves as an important way to hasten drug discovery. One promising approach to drug repositioning is to take advantage of machine learning (ML...

Tree-Based Learning of Regulatory Network Topologies and Dynamics with Jump3.

Methods in molecular biology (Clifton, N.J.)
Inference of gene regulatory networks (GRNs) from time series data is a well-established field in computational systems biology. Most approaches can be broadly divided in two families: model-based and model-free methods. These two families are highly...

Machine-learning-based patient-specific prediction models for knee osteoarthritis.

Nature reviews. Rheumatology
Osteoarthritis (OA) is an extremely common musculoskeletal disease. However, current guidelines are not well suited for diagnosing patients in the early stages of disease and do not discriminate patients for whom the disease might progress rapidly. T...