AIMC Topic: Machine Learning

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PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework.

Journal of theoretical biology
Determining the catalytic residues in an enzyme is critical to our understanding the relationship between protein sequence, structure, function, and enhancing our ability to design novel enzymes and their inhibitors. Although many enzymes have been s...

Development of CDK-targeted scoring functions for prediction of binding affinity.

Biophysical chemistry
Cyclin-dependent kinase (CDK) is an interesting biological macromolecule due to its role in cell cycle progression, transcription control, and neuronal development, to mention the most studied biological activities. Furthermore, the availability of h...

Hit Dexter: A Machine-Learning Model for the Prediction of Frequent Hitters.

ChemMedChem
False-positive assay readouts caused by badly behaving compounds-frequent hitters, pan-assay interference compounds (PAINS), aggregators, and others-continue to pose a major challenge to experimental screening. There are only a few in silico methods ...

Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application-Part 1: From Methodology to Clinical Implementation.

Journal of the American College of Radiology : JACR
Enterprise imaging has channeled various technological innovations to the field of clinical radiology, ranging from advanced imaging equipment and postacquisition iterative reconstruction tools to image analysis and computer-aided detection tools. Mo...

Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application-Part 2: From Clinical Implementation to Enterprise.

Journal of the American College of Radiology : JACR
Enterprise imaging has channeled various technological innovations to the field of clinical radiology, ranging from advanced imaging equipment and postacquisition iterative reconstruction tools to image analysis and computer-aided detection tools. Mo...

Anytime multipurpose emotion recognition from EEG data using a Liquid State Machine based framework.

Artificial intelligence in medicine
Recent technological advances in machine learning offer the possibility of decoding complex datasets and discern latent patterns. In this study, we adopt Liquid State Machines (LSM) to recognize the emotional state of an individual based on EEG data....

A Systematic Machine Learning Based Approach for the Diagnosis of Non-Alcoholic Fatty Liver Disease Risk and Progression.

Scientific reports
Prevention and diagnosis of NAFLD is an ongoing area of interest in the healthcare community. Screening is complicated by the fact that the accuracy of noninvasive testing lacks specificity and sensitivity to make and stage the diagnosis. Currently n...

Detection of sleep disordered breathing severity using acoustic biomarker and machine learning techniques.

Biomedical engineering online
PURPOSE: Breathing sounds during sleep are altered and characterized by various acoustic specificities in patients with sleep disordered breathing (SDB). This study aimed to identify acoustic biomarkers indicative of the severity of SDB by analyzing ...

A review of influenza detection and prediction through social networking sites.

Theoretical biology & medical modelling
Early prediction of seasonal epidemics such as influenza may reduce their impact in daily lives. Nowadays, the web can be used for surveillance of diseases. Search engines and social networking sites can be used to track trends of different diseases ...

Leukocyte Image Segmentation Using Novel Saliency Detection Based on Positive Feedback of Visual Perception.

Journal of healthcare engineering
This paper presents a novel method for salient object detection in nature image by simulating microsaccades in fixational eye movements. Due to a nucleated cell usually stained that is salient obviously, the proposed method is suitable to segment nuc...