AIMC Topic: Algorithms

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On the critical review of five machine learning-based algorithms for predicting protein stability changes upon mutation.

Briefings in bioinformatics
A review, recently published in this journal by Fang (2019), showed that methods trained for the prediction of protein stability changes upon mutation have a very critical bias: they neglect that a protein variation (A- > B) and its reverse (B- > A) ...

Powerlifting score prediction using a machine learning method.

Mathematical biosciences and engineering : MBE
This research discusses an interesting topic, using artificial intelligence methods to predict the score of powerlifters. We collected the characteristics of powerlifters, and then used the reservoir computing extreme learning machine to build a pred...

[Random survival forest: applying machine learning algorithm in survival analysis of biomedical data].

Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]
Traditional survival methods have a wide application in the field of biomedical research. However, applying traditional survival methods requires data to meet a set of special assumptions while the Random Survival Forest model can overcome this incon...

Predicting the fMRI Signal Fluctuation with Recurrent Neural Networks Trained on Vascular Network Dynamics.

Cerebral cortex (New York, N.Y. : 1991)
Resting-state functional MRI (rs-fMRI) studies have revealed specific low-frequency hemodynamic signal fluctuations (<0.1 Hz) in the brain, which could be related to neuronal oscillations through the neurovascular coupling mechanism. Given the vascul...

Deep learning with transfer learning in pathology. Case study: classification of basal cell carcinoma.

Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologie
Establishing basal cell carcinoma (BCC) subtype is sometimes challenging for pathologists. Deep-learning (DL) algorithms are an emerging approach in image classification due to their performance, accompanied by a new concept - transfer learning, whic...

Gene Classification Based on Multi-Class SVMs with Systematic Sampling and Hierarchical Clustering (SSHC) Algorithm.

Advances in experimental medicine and biology
The support vector machines (SVMs) is one of the machine learning algorithms with high classification accuracy. However, the support vector machine algorithm has a very high training complexity. Thus, it is not very efficient with large datasets. In ...

Web-Based Decision Support System for Coronary Heart Disease Diagnosis.

Advances in experimental medicine and biology
Coronary heart disease is a serious and common disease that affects a large part of the population. There is a tendency to use machine learning techniques for the punctual and valid diagnosis, which can determine the effectiveness of treatment and th...

Prediction of Blood Glucose Concentration Based on CEEMD and Improved Particle Swarm Optimization LSSVM.

Critical reviews in biomedical engineering
Aiming at the difficulty of accurate prediction due to the randomness and nonstationary nature of blood glucose concentration series, a blood glucose concentration prediction model based on complementary ensemble empirical mode decomposition (CEEMD) ...

Cone Beam CT (CBCT) Based Synthetic CT Generation Using Deep Learning Methods for Dose Calculation of Nasopharyngeal Carcinoma Radiotherapy.

Technology in cancer research & treatment
To generate synthetic CT (sCT) images with high quality from CBCT and planning CT (pCT) for dose calculation by using deep learning methods. 169 NPC patients with a total of 20926 slices of CBCT and pCT images were included. In this study the Cycle...