AIMC Topic:
Predictive Value of Tests

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Feature selective temporal prediction of Alzheimer's disease progression using hippocampus surface morphometry.

Brain and behavior
INTRODUCTION: Prediction of Alzheimer's disease (AD) progression based on baseline measures allows us to understand disease progression and has implications in decisions concerning treatment strategy. To this end, we combine a predictive multi-task m...

Text Mining of the Electronic Health Record: An Information Extraction Approach for Automated Identification and Subphenotyping of HFpEF Patients for Clinical Trials.

Journal of cardiovascular translational research
Precision medicine requires clinical trials that are able to efficiently enroll subtypes of patients in whom targeted therapies can be tested. To reduce the large amount of time spent screening, identifying, and recruiting patients with specific subt...

Medical image classification based on multi-scale non-negative sparse coding.

Artificial intelligence in medicine
With the rapid development of modern medical imaging technology, medical image classification has become more and more important in medical diagnosis and clinical practice. Conventional medical image classification algorithms usually neglect the sema...

Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning.

Scientific reports
Protein-protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large ...

Learning to Predict Consequences as a Method of Knowledge Transfer in Reinforcement Learning.

IEEE transactions on neural networks and learning systems
The reinforcement learning (RL) paradigm allows agents to solve tasks through trial-and-error learning. To be capable of efficient, long-term learning, RL agents should be able to apply knowledge gained in the past to new tasks they may encounter in ...

Automatic feature learning using multichannel ROI based on deep structured algorithms for computerized lung cancer diagnosis.

Computers in biology and medicine
This study aimed to analyze the ability of extracting automatically generated features using deep structured algorithms in lung nodule CT image diagnosis, and compare its performance with traditional computer aided diagnosis (CADx) systems using hand...

The way to cover prediction for cytotoxicity for all existing nano-sized metal oxides by using neural network method.

Nanotoxicology
The regulatory agencies should fulfil the data gap in toxicity for new chemicals including nano-sized compounds, like metal oxides nanoparticles (MeO NPs) according to the registration, evaluation, authorisation and restriction of chemicals (REACH) l...

Feasibility of spirography features for objective assessment of motor function in Parkinson's disease.

Artificial intelligence in medicine
OBJECTIVE: Parkinson's disease (PD) is currently incurable, however proper treatment can ease the symptoms and significantly improve the quality of life of patients. Since PD is a chronic disease, its efficient monitoring and management is very impor...