Recent applications of machine learning in medicinal chemistry
J Panteleev, H Gao, L Jia - Bioorganic & medicinal chemistry letters, 2018 - Elsevier
In recent decades, artificial intelligence and machine learning have played a significant role
in increasing the efficiency of processes across a wide spectrum of industries. When it …
in increasing the efficiency of processes across a wide spectrum of industries. When it …
Evolving deep echo state networks for intelligent fault diagnosis
Echo state network (ESN) is a fast recurrent neural network with remarkable generalization
performance for intelligent diagnosis of machinery faults. When dealing with high …
performance for intelligent diagnosis of machinery faults. When dealing with high …
Human activity recognition from sensor data using spatial attention-aided CNN with genetic algorithm
A Sarkar, SKS Hossain, R Sarkar - Neural Computing and Applications, 2023 - Springer
Capturing time and frequency relationships of time series signals offers an inherent barrier
for automatic human activity recognition (HAR) from wearable sensor data. Extracting …
for automatic human activity recognition (HAR) from wearable sensor data. Extracting …
C-HMOSHSSA: Gene selection for cancer classification using multi-objective meta-heuristic and machine learning methods
Background and objective: Over the last two decades, DNA microarray technology has
emerged as a powerful tool for early cancer detection and prevention. It helps to provide a …
emerged as a powerful tool for early cancer detection and prevention. It helps to provide a …
A survey on reservoir computing and its interdisciplinary applications beyond traditional machine learning
Reservoir computing (RC), first applied to temporal signal processing, is a recurrent neural
network in which neurons are randomly connected. Once initialized, the connection …
network in which neurons are randomly connected. Once initialized, the connection …
Gene selection for cancer types classification using novel hybrid metaheuristics approach
With the advancement of microarray technology, gene expression profiling has shown
remarkable effort to predict the different types of malignancy and their subtypes. In …
remarkable effort to predict the different types of malignancy and their subtypes. In …
An efficient high-dimensional gene selection approach based on the Binary Horse Herd Optimization Algorithm for biologicaldata classification
Abstract The Horse Herd Optimization Algorithm (HOA) is a new meta-heuristic algorithm
inspired by the behaviors of horses of different ages. It was recently introduced to solve …
inspired by the behaviors of horses of different ages. It was recently introduced to solve …
Using deep learning with bayesian–Gaussian inspired convolutional neural architectural search for cancer recognition and classification from histopathological image …
We propose a neural architectural search model which examines histopathological images
to detect the presence of cancer in both lung and colon tissues. In recent times, deep …
to detect the presence of cancer in both lung and colon tissues. In recent times, deep …
BE-DTI': Ensemble framework for drug target interaction prediction using dimensionality reduction and active learning
Background and objective Drug-target interaction prediction plays an intrinsic role in the
drug discovery process. Prediction of novel drugs and targets helps in identifying optimal …
drug discovery process. Prediction of novel drugs and targets helps in identifying optimal …
Drug sensitivity prediction framework using ensemble and multi-task learning
Radiation and hormone level targeted drug therapy are one of the most widely adopted
treatment options for different types of cancer. But, due to genetic variations, cancer patients …
treatment options for different types of cancer. But, due to genetic variations, cancer patients …