AI Medical Compendium Topic

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Machine Learning Techniques for Prediction of Early Childhood Obesity.

Applied clinical informatics
OBJECTIVES: This paper aims to predict childhood obesity after age two, using only data collected prior to the second birthday by a clinical decision support system called CHICA.

The potential of random forest and neural networks for biomass and recombinant protein modeling in Escherichia coli fed-batch fermentations.

Biotechnology journal
Product quality assurance strategies in production of biopharmaceuticals currently undergo a transformation from empirical "quality by testing" to rational, knowledge-based "quality by design" approaches. The major challenges in this context are the ...

SFM: A novel sequence-based fusion method for disease genes identification and prioritization.

Journal of theoretical biology
The identification of disease genes from human genome is of great importance to improve diagnosis and treatment of disease. Several machine learning methods have been introduced to identify disease genes. However, these methods mostly differ in the p...

Binding Activity Prediction of Cyclin-Dependent Inhibitors.

Journal of chemical information and modeling
The Cyclin-Dependent Kinases (CDKs) are the core components coordinating eukaryotic cell division cycle. Generally the crystal structure of CDKs provides information on possible molecular mechanisms of ligand binding. However, reliable and robust est...

Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets.

PloS one
Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not...

A k-mer-based barcode DNA classification methodology based on spectral representation and a neural gas network.

Artificial intelligence in medicine
OBJECTIVES: In this paper, an alignment-free method for DNA barcode classification that is based on both a spectral representation and a neural gas network for unsupervised clustering is proposed.

Recognition of activities of daily living in healthy subjects using two ad-hoc classifiers.

Biomedical engineering online
BACKGROUND: Activities of daily living (ADL) are important for quality of life. They are indicators of cognitive health status and their assessment is a measure of independence in everyday living. ADL are difficult to reliably assess using questionna...

Differential diagnosis of pleural mesothelioma using Logic Learning Machine.

BMC bioinformatics
BACKGROUND: Tumour markers are standard tools for the differential diagnosis of cancer. However, the occurrence of nonspecific symptoms and different malignancies involving the same cancer site may lead to a high proportion of misclassifications. Cla...

Teaching a Machine to Feel Postoperative Pain: Combining High-Dimensional Clinical Data with Machine Learning Algorithms to Forecast Acute Postoperative Pain.

Pain medicine (Malden, Mass.)
BACKGROUND: Given their ability to process highly dimensional datasets with hundreds of variables, machine learning algorithms may offer one solution to the vexing challenge of predicting postoperative pain.