AIMC Topic: Machine Learning

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Contrastive representation learning of inorganic materials to overcome lack of training datasets.

Chemical communications (Cambridge, England) Jun 9, 2022
Data representation forms a feature space where forms data distribution that is one of the key factors determining the prediction accuracy of machine learning (ML). In particular, the data representation is crucial to handle small and biased training...
Machine Learning Software Algorithms
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A Complete Process of Text Classification System Using State-of-the-Art NLP Models.

Computational intelligence and neuroscience Jun 9, 2022
With the rapid advancement of information technology, online information has been exponentially growing day by day, especially in the form of text documents such as news events, company reports, reviews on products, stocks-related reports, medical re...
Machine Learning Algorithms Natural Language Processing Publications Data Mining
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Fuzzy Logic-Based Machine Learning Algorithm for Cultural and Creative Product Design.

Computational intelligence and neuroscience Jun 9, 2022
In order to effectively assist industrial designers in the color scheme design of cultural and creative products and output color schemes that meet users' image preferences, an interactive color scheme design method for cultural and creative products...
Machine Learning Algorithms Fuzzy Logic
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Multiclass Cancer Prediction Based on Copy Number Variation Using Deep Learning.

Computational intelligence and neuroscience Jun 9, 2022
DNA copy number variation (CNV) is the type of DNA variation which is associated with various human diseases. CNV ranges in size from 1 kilobase to several megabases on a chromosome. Most of the computational research for cancer classification is tra...
Humans Neural Networks, Computer Machine Learning Neoplasms Deep Learning DNA Copy Number Variations
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Modern Machine-Learning Predictive Models for Diagnosing Infectious Diseases.

Computational and mathematical methods in medicine Jun 9, 2022
Controlling infectious diseases is a major health priority because they can spread and infect humans, thus evolving into epidemics or pandemics. Therefore, early detection of infectious diseases is a significant need, and many researchers have develo...
Humans Machine Learning Pandemics Algorithms Communicable Diseases Big Data
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Using forensic analytics and machine learning to detect bribe payments in regime-switching environments: Evidence from the India demonetization.

PloS one Jun 9, 2022
We use a rich set of transaction data from a large retailer in India and a dataset on bribe payments to train random forest and XGBoost models using empirical measures guided by Benford's Law, a commonly used tool in forensic analytics. We evaluate t...
Machine Learning India Forensic Medicine
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Postoperative Intensive Care Unit Overtriage: An Application of Machine Learning.

Annals of surgery Jun 8, 2022
Humans Machine Learning Retrospective Studies Intensive Care Units Triage
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Commentary: Validation of Machine Learning-Based Automated Surgical Instrument Annotation Using Publicly Available Intraoperative Video.

Operative neurosurgery (Hagerstown, Md.) Jun 8, 2022
Humans Machine Learning Algorithms Surgical Instruments
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A machine learning model for separating epithelial and stromal regions in oral cavity squamous cell carcinomas using H&E-stained histology images: A multi-center, retrospective study.

Oral oncology Jun 8, 2022
OBJECTIVE: Tissue slides from Oral cavity squamous cell carcinoma (OC-SCC), particularly the epithelial regions, hold morphologic features that are both diagnostic and prognostic. Yet, previously developed approaches for automated epithelium segmenta...
Humans Machine Learning Retrospective Studies Carcinoma, Squamous Cell Deep Learning Image Processing, Computer-Assisted Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Mouth Neoplasms
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Organic Compound Synthetic Accessibility Prediction Based on the Graph Attention Mechanism.

Journal of chemical information and modeling Jun 8, 2022
Accurate estimation of the synthetic accessibility of small molecules is needed in many phases of drug discovery. Several expert-crafted scoring methods and descriptor-based quantitative structure-activity relationship (QSAR) models have been develop...
Neural Networks, Computer Machine Learning Drug Discovery Bayes Theorem Quantitative Structure-Activity Relationship
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