AIMC Topic: Algorithms

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Collaborative targeted learning using regression shrinkage.

Statistics in medicine
Causal inference practitioners are routinely presented with the challenge of model selection and, in particular, reducing the size of the covariate set with the goal of improving estimation efficiency. Collaborative targeted minimum loss-based estima...

Specific and intrinsic sequence patterns extracted by deep learning from intra-protein binding and non-binding peptide fragments.

Scientific reports
The key finding in the DNA double helix model is the specific pairing or binding between nucleotides A-T and C-G, and the pairing rules are the molecule basis of genetic code. Unfortunately, no such rules have been discovered for proteins. Here we sh...

Flood susceptibility assessment in Hengfeng area coupling adaptive neuro-fuzzy inference system with genetic algorithm and differential evolution.

The Science of the total environment
Floods are among Earth's most common natural hazards, and they cause major economic losses and seriously affect peoples' lives and health. This paper addresses the development of a flood susceptibility assessment that uses intelligent techniques and ...

Protein contact prediction by integrating deep multiple sequence alignments, coevolution and machine learning.

Proteins
In this study, we report the evaluation of the residue-residue contacts predicted by our three different methods in the CASP12 experiment, focusing on studying the impact of multiple sequence alignment, residue coevolution, and machine learning on co...

Prediction of protein subcellular localization with oversampling approach and Chou's general PseAAC.

Journal of theoretical biology
Predicting protein subcellular location with support vector machine has been a popular research area recently because of the dramatic explosion of bioinformation. Though substantial achievements have been obtained, few researchers considered the prob...

Supervised learning methods for pathological arterial pulse wave differentiation: A SVM and neural networks approach.

International journal of medical informatics
OBJECTIVE: The main goal of this study was to develop an automatic method based on supervised learning methods, able to distinguish healthy from pathologic arterial pulse wave (APW), and those two from noisy waveforms (non-relevant segments of the si...

Development of a Reinforcement Learning-based Evolutionary Fuzzy Rule-Based System for diabetes diagnosis.

Computers in biology and medicine
The early diagnosis of disease is critical to preventing the occurrence of severe complications. Diabetes is a serious health problem. A variety of methods have been developed for diagnosing diabetes. The majority of these methods have been developed...

Endoscopic Image Classification and Retrieval using Clustered Convolutional Features.

Journal of medical systems
With the growing use of minimally invasive surgical procedures, endoscopic video archives are growing at a rapid pace. Efficient access to relevant content in such huge multimedia archives require compact and discriminative visual features for indexi...

Long short-term memory RNN for biomedical named entity recognition.

BMC bioinformatics
BACKGROUND: Biomedical named entity recognition(BNER) is a crucial initial step of information extraction in biomedical domain. The task is typically modeled as a sequence labeling problem. Various machine learning algorithms, such as Conditional Ran...