AIMC Topic: Machine Learning

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Machine learning and deep learning enabled fuel sooting tendency prediction from molecular structure.

Journal of molecular graphics & modelling
Soot formation models become increasingly important in advanced renewable fuels formulation for soot reduction benefit. This work evaluates performance of machine learning (ML) and deep learning (DL) to predict yield sooting index (YSI) from chemical...

Federated personalized random forest for human activity recognition.

Mathematical biosciences and engineering : MBE
User data usually exists in the organization or own local equipment in the form of data island. It is difficult to collect these data to train better machine learning models because of the General Data Protection Regulation (GDPR) and other laws. The...

Class imbalance in out-of-distribution datasets: Improving the robustness of the TextCNN for the classification of rare cancer types.

Journal of biomedical informatics
In the last decade, the widespread adoption of electronic health record documentation has created huge opportunities for information mining. Natural language processing (NLP) techniques using machine and deep learning are becoming increasingly widesp...

Drug Design: Where We Are and Future Prospects.

Molecules (Basel, Switzerland)
Medicinal chemistry is facing new challenges in approaching precision medicine. Several powerful new tools or improvements of already used tools are now available to medicinal chemists to help in the process of drug discovery, from a hit molecule to ...

Detecting immunotherapy-sensitive subtype in gastric cancer using histologic image-based deep learning.

Scientific reports
Immune checkpoint inhibitor (ICI) therapy is widely used but effective only in a subset of gastric cancers. Epstein-Barr virus (EBV)-positive and microsatellite instability (MSI) / mismatch repair deficient (dMMR) tumors have been reported to be high...

The new SUMPOT to predict postoperative complications using an Artificial Neural Network.

Scientific reports
An accurate assessment of preoperative risk may improve use of hospital resources and reduce morbidity and mortality in high-risk surgical patients. This study aims at implementing an automated surgical risk calculator based on Artificial Neural Netw...

A unified drug-target interaction prediction framework based on knowledge graph and recommendation system.

Nature communications
Prediction of drug-target interactions (DTI) plays a vital role in drug development in various areas, such as virtual screening, drug repurposing and identification of potential drug side effects. Despite extensive efforts have been invested in perfe...

Improving random forest predictions in small datasets from two-phase sampling designs.

BMC medical informatics and decision making
BACKGROUND: While random forests are one of the most successful machine learning methods, it is necessary to optimize their performance for use with datasets resulting from a two-phase sampling design with a small number of cases-a common situation i...

Application of Digital Image Based on Machine Learning in Media Art Design.

Computational intelligence and neuroscience
In digital media art, expressive force is an important art form of media. This paper studies digital images that have the same effect when applied to media art. The research object is media art images, and the application effect of the proposed algor...

FWNNet: Presentation of a New Classifier of Brain Tumor Diagnosis Based on Fuzzy Logic and the Wavelet-Based Neural Network Using Machine-Learning Methods.

Computational intelligence and neuroscience
In this paper, we present a novel classifier based on fuzzy logic and wavelet transformation in the form of a neural network. This classifier includes a layer to predict the numerical feature corresponded to labels or classes. The presented classifie...