AIMC Topic: Machine Learning

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Medical Image Analysis Using AM-FM Models and Methods.

IEEE reviews in biomedical engineering
Medical image analysis methods require the use of effective representations for differentiating between lesions, diseased regions, and normal structure. Amplitude Modulation-Frequency Modulation (AM-FM) models provide effective representations throug...

Machine learning combining CT findings and clinical parameters improves prediction of length of stay and ICU admission in torso trauma.

European radiology
OBJECTIVE: To develop machine learning (ML) models capable of predicting ICU admission and extended length of stay (LOS) after torso (chest, abdomen, or pelvis) trauma, by using clinical and/or imaging data.

Modeling autosomal dominant Alzheimer's disease with machine learning.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Machine learning models were used to discover novel disease trajectories for autosomal dominant Alzheimer's disease.

Natural language processing was effective in assisting rapid title and abstract screening when updating systematic reviews.

Journal of clinical epidemiology
BACKGROUND AND OBJECTIVE: To examine whether the use of natural language processing (NLP) technology is effective in assisting rapid title and abstract screening when updating a systematic review.

A high-throughput and machine learning resistance monitoring system to determine the point of resistance for Escherichia coli with tetracycline: Combining UV-visible spectrophotometry with principal component analysis.

Biotechnology and bioengineering
UV-visible spectroscopy (UV-Vis) is routinely used in microbiology as a tool to check the optical density (OD) pertaining to the growth stages of microbial cultures at the single wavelength of 600 nm, better known as the OD . Typically, modern UV-Vis...

Ensemble-AMPPred: Robust AMP Prediction and Recognition Using the Ensemble Learning Method with a New Hybrid Feature for Differentiating AMPs.

Genes
Antimicrobial peptides (AMPs) are natural peptides possessing antimicrobial activities. These peptides are important components of the innate immune system. They are found in various organisms. AMP screening and identification by experimental techniq...

Repeatability and reproducibility study of radiomic features on a phantom and human cohort.

Scientific reports
The repeatability and reproducibility of radiomic features extracted from CT scans need to be investigated to evaluate the temporal stability of imaging features with respect to a controlled scenario (test-retest), as well as their dependence on acqu...

Ranking of a wide multidomain set of predictor variables of children obesity by machine learning variable importance techniques.

Scientific reports
The increased prevalence of childhood obesity is expected to translate in the near future into a concomitant soaring of multiple cardio-metabolic diseases. Obesity has a complex, multifactorial etiology, that includes multiple and multidomain potenti...

Asthma-prone areas modeling using a machine learning model.

Scientific reports
Nowadays, owing to population growth, increasing environmental pollution, and lifestyle changes, the number of asthmatics has significantly increased. Therefore, the purpose of our study was to determine the asthma-prone areas in Tehran, Iran conside...