AIMC Topic: Machine Learning

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A Validation Study of Freezing of Gait (FoG) Detection and Machine-Learning-Based FoG Prediction Using Estimated Gait Characteristics with a Wearable Accelerometer.

Sensors (Basel, Switzerland)
One of the most common symptoms observed among most of the Parkinson's disease patients that affects movement pattern and is also related to the risk of fall, is usually termed as "freezing of gait (FoG)". To allow systematic assessment of FoG, objec...

Determining Pain Catastrophizing From Daily Pain App Assessment Data: Role of Computer-Based Classification.

The journal of pain
This study compared persons with chronic pain who consistently reported that their pain was worsening with those who reported that their pain was improving or remaining the same per daily assessment data from a smartphone pain app. All participants c...

DrugMetab: An Integrated Machine Learning and Lexicon Mapping Named Entity Recognition Method for Drug Metabolite.

CPT: pharmacometrics & systems pharmacology
Drug metabolites (DMs) are critical in pharmacology research areas, such as drug metabolism pathways and drug-drug interactions. However, there is no terminology dictionary containing comprehensive drug metabolite names, and there is no named entity ...

Optical classification of neoplastic colorectal polyps - a computer-assisted approach (the COACH study).

Scandinavian journal of gastroenterology
BACKGROUND AND AIMS: Clinical data suggest that the quality of optical diagnoses of colorectal polyps differs markedly among endoscopists. The aim of this study was to develop a computer program that was able to differentiate neoplastic from non-neop...

A Hybrid Feature Selection Method Based on Binary State Transition Algorithm and ReliefF.

IEEE journal of biomedical and health informatics
Feature selection problems often appear in the application of data mining, which have been difficult to handle due to the NP-hard property of these problems. In this study, a simple but efficient hybrid feature selection method is proposed based on b...

Feasibility of anatomical feature points for the estimation of prostate locations in the Bayesian delineation frameworks for prostate cancer radiotherapy.

Radiological physics and technology
This study aimed to investigate the feasibility of anatomical feature points for the estimation of prostate locations in the Bayesian delineation frameworks for prostate cancer radiotherapy. The relationships between the reference centroids of prosta...

A soft artificial muscle driven robot with reinforcement learning.

Scientific reports
Soft robots driven by stimuli-responsive materials have their own unique advantages over traditional rigid robots such as large actuation, light weight, good flexibility and biocompatibility. However, the large actuation of soft robots inherently co-...

Variable importance for sustaining macrophyte presence via random forests: data imputation and model settings.

Scientific reports
Data sets plagued with missing data and performance-affecting model parameters represent recurrent issues within the field of data mining. Via random forests, the influence of data reduction, outlier and correlated variable removal and missing data i...

Large-scale protein function prediction using heterogeneous ensembles.

F1000Research
Heterogeneous ensembles are an effective approach in scenarios where the ideal data type and/or individual predictor are unclear for a given problem. These ensembles have shown promise for protein function prediction (PFP), but their ability to impro...

Predictive classifier models built from natural products with antimalarial bioactivity using machine learning approach.

PloS one
In view of the vast number of natural products with potential antiplasmodial bioactivity and cost of conducting antiplasmodial bioactivity assays, it may be judicious to learn from previous antiplasmodial bioassays and predict bioactivity of these na...