AIMC Topic: Machine Learning

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Metabolic pathway inference using multi-label classification with rich pathway features.

PLoS computational biology
Metabolic inference from genomic sequence information is a necessary step in determining the capacity of cells to make a living in the world at different levels of biological organization. A common method for determining the metabolic potential encod...

Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analyses.

BMC bioinformatics
BACKGROUND: A typical task in bioinformatics consists of identifying which features are associated with a target outcome of interest and building a predictive model. Automated machine learning (AutoML) systems such as the Tree-based Pipeline Optimiza...

Artificial intelligence in pulmonary medicine: computer vision, predictive model and COVID-19.

European respiratory review : an official journal of the European Respiratory Society
Artificial intelligence (AI) is transforming healthcare delivery. The digital revolution in medicine and healthcare information is prompting a staggering growth of data intertwined with elements from many digital sources such as genomics, medical ima...

Advancing predictive modeling in archaeology: An evaluation of regression and machine learning methods on the Grand Staircase-Escalante National Monument.

PloS one
Predictive models are central to both archaeological research and cultural resource management. Yet, archaeological applications of predictive models are often insufficient due to small training data sets, inadequate statistical techniques, and a lac...

Citation screening using crowdsourcing and machine learning produced accurate results: Evaluation of Cochrane's modified Screen4Me service.

Journal of clinical epidemiology
OBJECTIVES: To assess the feasibility of a modified workflow that uses machine learning and crowdsourcing to identify studies for potential inclusion in a systematic review.

Human-machine alliance against cervical cancer.

International journal of gynecological cancer : official journal of the International Gynecological Cancer Society

Can machine learning be useful as a screening tool for depression in primary care?

Journal of psychiatric research
Depression is a widespread disease with a high economic burden and a complex pathophysiology disease that is still not wholly clarified, not to mention it usually is associated as a risk factor for absenteeism at work and suicide. Just 50% of patient...

Machine learning-based data analytic approaches for evaluating post-natal mouse respiratory physiological evolution.

Respiratory physiology & neurobiology
Respiratory parameters change during post-natal development, but the nature of their changes have not been well-described. The advent of commercially available plethysmographic instruments provided improved repeatability of measurements and standardi...

[Big Data, AI and Machine Learning for Precision Psychiatry: How are they changing the clinical practice?].

Fortschritte der Neurologie-Psychiatrie
Currently, we are witnessing an increasing interest in predictive models and personalized diagnosis and treatment choice in psychiatric research. Against this background, the emerging field of Precision Psychiatry is trying to establish precise diagn...

Classification and Quantification of Microplastics (<100 μm) Using a Focal Plane Array-Fourier Transform Infrared Imaging System and Machine Learning.

Analytical chemistry
Microplastics are defined as microscopic plastic particles in the range from few micrometers and up to 5 mm. These small particles are classified as primary microplastics when they are manufactured in this size range, whereas secondary microplastics ...