AIMC Topic: Algorithms

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Automated Neuron Detection in High-Content Fluorescence Microscopy Images Using Machine Learning.

Neuroinformatics
The study of neuronal morphology in relation to function, and the development of effective medicines to positively impact this relationship in patients suffering from neurodegenerative diseases, increasingly involves image-based high-content screenin...

MySurgeryRisk: Development and Validation of a Machine-learning Risk Algorithm for Major Complications and Death After Surgery.

Annals of surgery
OBJECTIVE: To accurately calculate the risk for postoperative complications and death after surgery in the preoperative period using machine-learning modeling of clinical data.

[Automatic Identifcation of Heart Block Precise Location Based on Sparse Connection Residual Network].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
OBJECTIVE: To classify Right Bundle Branch Block (RBBB),Left Bundle Branch Block (LBBB) and normal ECG signals automatically.

TKRD: Trusted kernel rootkit detection for cybersecurity of VMs based on machine learning and memory forensic analysis.

Mathematical biosciences and engineering : MBE
The promotion of cloud computing makes the virtual machine (VM) increasingly a target of malware attacks in cybersecurity such as those by kernel rootkits. Memory forensic, which observes the malicious tracks from the memory aspect, is a useful way f...

A new deep learning model for assisted diagnosis on electrocardiogram.

Mathematical biosciences and engineering : MBE
In order to enhance the accuracy of computer aided electrocardiogram analysis, we propose a deep learning model called CBRNN to assist diagnosis on electrocardiogram for clinical medical service. It combines two sub networks which are convolutional n...

Identification of hormone binding proteins based on machine learning methods.

Mathematical biosciences and engineering : MBE
The soluble carrier hormone binding protein (HBP) plays an important role in the growth of human and other animals. HBP can also selectively and non-covalently interact with hormone. Therefore, accurate identification of HBP is an important prerequis...

Machine learning approaches to decipher hormone and HER2 receptor status phenotypes in breast cancer.

Briefings in bioinformatics
Breast cancer prognosis and administration of therapies are aided by knowledge of hormonal and HER2 receptor status. Breast cancer lacking estrogen receptors, progesterone receptors and HER2 receptors are difficult to treat. Regarding large data repo...

miES: predicting the essentiality of miRNAs with machine learning and sequence features.

Bioinformatics (Oxford, England)
MOTIVATION: MicroRNAs (miRNAs) are one class of small noncoding RNA molecules, which regulate gene expression at the post-transcriptional level and play important roles in health and disease. To dissect the critical miRNAs in miRNAome, it is needed t...

Automated Diagnosis of Lymphoma with Digital Pathology Images Using Deep Learning.

Annals of clinical and laboratory science
Recent studies have shown promising results in using Deep Learning to detect malignancy in whole slide imaging, however, they were limited to just predicting a positive or negative finding for a specific neoplasm. We attempted to use Deep Learning wi...

[Machine Learning Applications in Cancer Genome Medicine].

Gan to kagaku ryoho. Cancer & chemotherapy
Practical cancer genome medicine requires large-scale data analysis for many types of biological data such as cancer driver mutations, aberrantly methylated regions, gene expression also biological knowledge from literature. Machine learning algorith...