AIMC Topic: Machine Learning

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Explainable artificial intelligence in forensics: Realistic explanations for number of contributor predictions of DNA profiles.

Forensic science international. Genetics
Machine learning obtains good accuracy in determining the number of contributors (NOC) in short tandem repeat (STR) mixture DNA profiles. However, the models used so far are not understandable to users as they only output a prediction without any rea...

Accurate classification of Listeria species by MALDI-TOF mass spectrometry incorporating denoising autoencoder and machine learning.

Journal of microbiological methods
Listeria monocytogenes belongs to the category of facultative anaerobic bacteria, and is the pathogen of listeriosis, potentially lethal disease for humans. There are many similarities between L. monocytogenes and other non-pathogenic Listeria specie...

The Role of Machine Learning in Cardiovascular Pathology.

The Canadian journal of cardiology
Machine learning has seen slow but steady uptake in diagnostic pathology over the past decade to assess digital whole-slide images. Machine learning tools have incredible potential to standardise, and likely even improve, histopathologic diagnoses, b...

Spatial and temporal dynamics of RhoA activities of single breast tumor cells in a 3D environment revealed by a machine learning-assisted FRET technique.

Experimental cell research
One of the hallmarks of cancer cells is their exceptional ability to migrate within the extracellular matrix (ECM) for gaining access to the circulatory system, a critical step of cancer metastasis. RhoA, a small GTPase, is known to be a key molecula...

Inter-patient automated arrhythmia classification: A new approach of weight capsule and sequence to sequence combination.

Computer methods and programs in biomedicine
OBJECTIVE: We propose a new capsule network to compensate for the information loss in the deep convolutional networks in previous studies, and to improve the performance of arrhythmia classification.

Comparison of machine learning and deep learning for view identification from cardiac magnetic resonance images.

Clinical imaging
BACKGROUND: Artificial intelligence is increasingly utilized to aid in the interpretation of cardiac magnetic resonance (CMR) studies. One of the first steps is the identification of the imaging plane depicted, which can be achieved by both deep lear...

O-glycosylation site prediction for by combining properties and sequence features with support vector machine.

Journal of bioinformatics and computational biology
O-glycosylation is a protein posttranslational modification important in regulating almost all cells. It is related to a large number of physiological and pathological phenomena. Recognizing O-glycosylation sites is the key to further investigating t...

Machine learning approach for predicting the antifungal effect of gilaburu (Viburnum opulus) fruit extracts on Fusarium spp. isolated from diseased potato tubers.

Journal of microbiological methods
This work addresses the mathematical model building to detect the diameter of the inhibition zone of gilaburu (Viburnum opulus L.) extract against eight different Fusarium strains isolated from diseased potato tubers. Gilaburu extracts were obtained ...

Natural Language Processing Enhances Prediction of Functional Outcome After Acute Ischemic Stroke.

Journal of the American Heart Association
Background Conventional prognostic scores usually require predefined clinical variables to predict outcome. The advancement of natural language processing has made it feasible to derive meaning from unstructured data. We aimed to test whether using u...

New Models to Predict the Acute and Chronic Toxicities of Representative Species of the Main Trophic Levels of Aquatic Environments.

Molecules (Basel, Switzerland)
To assess the impact of chemicals on an aquatic environment, toxicological data for three trophic levels are needed to address the chronic and acute toxicities. The use of non-testing methods, such as predictive computational models, was proposed to ...