AIMC Topic: Machine Learning

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A Molecular Image-Based Novel Quantitative Structure-Activity Relationship Approach, Deepsnap-Deep Learning and Machine Learning.

Current issues in molecular biology
The quantitative structure-activity relationship (QSAR) approach has been used in numerous chemical compounds as computational assessment for a long time. Further, owing to the high-performance modeling of QSAR, machine learning methods have been de...

Addressing Noise and Skewness in Interpretable Health-Condition Assessment by Learning Model Confidence.

Sensors (Basel, Switzerland)
Assessing the health condition has a wide range of applications in healthcare, military, aerospace, and industrial fields. Nevertheless, traditional feature-engineered techniques involve manual feature extraction, which are too cumbersome to adapt to...

Systems biology in cardiovascular disease: a multiomics approach.

Nature reviews. Cardiology
Omics techniques generate large, multidimensional data that are amenable to analysis by new informatics approaches alongside conventional statistical methods. Systems theories, including network analysis and machine learning, are well placed for anal...

Machine Learning Feature Selection for Predicting High Concentration Therapeutic Antibody Aggregation.

Journal of pharmaceutical sciences
Protein aggregation can hinder the development, safety and efficacy of therapeutic antibody-based drugs. Developing a predictive model that evaluates aggregation behaviors during early stage development is therefore desirable. Machine learning is a w...

Imaging Beyond Seeing: Early Prognosis of Cancer Treatment.

Small methods
Assessing cancer response to therapeutic interventions has been realized as an important course to early predict curative efficacy and treatment outcomes due to tumor heterogeneity. Compared to the traditional invasive tissue biopsy method, molecular...

Application of machine learning to improve dairy farm management: A systematic literature review.

Preventive veterinary medicine
In recent years, several researchers and practitioners applied machine learning algorithms in the dairy farm context and discussed several solutions to predict various variables of interest, most of which were related to incipient diseases. The objec...

Modeling the human aging transcriptome across tissues, health status, and sex.

Aging cell
Aging in humans is an incredibly complex biological process that leads to increased susceptibility to various diseases. Understanding which genes are associated with healthy aging can provide valuable insights into aging mechanisms and possible avenu...

Multi-task learning for the simultaneous reconstruction of the human and mouse gene regulatory networks.

Scientific reports
The reconstruction of Gene Regulatory Networks (GRNs) from gene expression data, supported by machine learning approaches, has received increasing attention in recent years. The task at hand is to identify regulatory links between genes in a network....

Assessment of skin barrier function using skin images with topological data analysis.

NPJ systems biology and applications
Recent developments of molecular biology have revealed diverse mechanisms of skin diseases, and precision medicine considering these mechanisms requires the frequent objective evaluation of skin phenotypes. Transepidermal water loss (TEWL) is commonl...