AIMC Topic: Machine Learning

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Protein p Prediction by Tree-Based Machine Learning.

Journal of chemical theory and computation
Protonation states of ionizable protein residues modulate many essential biological processes. For correct modeling and understanding of these processes, it is crucial to accurately determine their p values. Here, we present four tree-based machine l...

Prediction of Maximum Absorption Wavelength Using Deep Neural Networks.

Journal of chemical information and modeling
Fluorescent molecules are important tools in biological detection, and numerous efforts have been made to develop compounds to meet the desired photophysical properties. For example, tuning the wavelength allows an appropriate penetration depth with ...

Artificial Intelligence Algorithms for Malware Detection in Android-Operated Mobile Devices.

Sensors (Basel, Switzerland)
With the rapid expansion of the use of smartphone devices, malicious attacks against Android mobile devices have increased. The Android system adopted a wide range of sensitive applications such as banking applications; therefore, it is becoming the ...

Graph-Powered Interpretable Machine Learning Models for Abnormality Detection in Ego-Things Network.

Sensors (Basel, Switzerland)
In recent days, it is becoming essential to ensure that the outcomes of signal processing methods based on machine learning (ML) data-driven models can provide interpretable predictions. The interpretability of ML models can be defined as the capabil...

A Contrastive Predictive Coding-Based Classification Framework for Healthcare Sensor Data.

Journal of healthcare engineering
Supervised learning technologies have been used in medical-data classification to improve diagnosis efficiency and reduce human diagnosis errors. A large amount of manually annotated data are required for the fully supervised learning process. Howeve...

English Text Readability Measurement Based on Convolutional Neural Network: A Hybrid Network Model.

Computational intelligence and neuroscience
Text readability is very important in meeting people's information needs. With the explosive growth of modern information, the measurement demand of text readability is increasing. In view of the text structure of words, sentences, and texts, a hybri...

Human Resource Planning and Configuration Based on Machine Learning.

Computational intelligence and neuroscience
Human resources are the core resources of an enterprise, and the demand forecasting plays a vital role in the allocation and optimization of human resources. Starting from the basic concepts of human resource forecasting, this paper employs the backp...

Oncological drug discovery: AI meets structure-based computational research.

Drug discovery today
The integration of machine learning and structure-based methods has proven valuable in the past as a way to prioritize targets and compounds in early drug discovery. In oncological research, these methods can be highly beneficial in addressing the di...

Atomistic Simulations for Reactions and Vibrational Spectroscopy in the Era of Machine Learning─

The journal of physical chemistry. B
Atomistic simulations using accurate energy functions can provide molecular-level insight into functional motions of molecules in the gas and in the condensed phase. This Perspective delineates the present status of the field from the efforts of othe...

Effectiveness of Artificial Neural Networks for Solving Inverse Problems in Magnetic Field-Based Localization.

Sensors (Basel, Switzerland)
Recently, indoor localization has become an active area of research. Although there are various approaches to indoor localization, methods that utilize artificially generated magnetic fields from a target device are considered to be the best in terms...