AIMC Topic: Algorithms

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A low-cost machine learning framework for predicting drug-drug interactions based on fusion of multiple features and a parameter self-tuning strategy.

Physical chemistry chemical physics : PCCP
Poly-drug therapy is now recognized as a crucial treatment, and the analysis of drug-drug interactions (DDIs) offers substantial theoretical support and guidance for its implementation. Predicting potential DDIs using intelligent algorithms is an eme...

Stabilization and tracking control of underactuated ball and beam system using metaheuristic optimization based TID-F and PIDD2-PI control schemes.

PloS one
In this paper, we propose two different control strategies for the position control of the ball of the ball and beam system (BBS). The first control strategy uses the proportional integral derivative-second derivative with a proportional integrator P...

Enhancing machine learning-based sentiment analysis through feature extraction techniques.

PloS one
A crucial part of sentiment classification is featuring extraction because it involves extracting valuable information from text data, which affects the model's performance. The goal of this paper is to help in selecting a suitable feature extraction...

A comprehensive review of machine learning and its application to dairy products.

Critical reviews in food science and nutrition
Machine learning (ML) technology is a powerful tool in food science and engineering offering numerous advantages, from recognizing patterns and predicting outcomes to customizing and adjusting to individual needs. Its further development can enable r...

Accurate Liver Fibrosis Detection Through Hybrid MRMR-BiLSTM-CNN Architecture with Histogram Equalization and Optimization.

Journal of imaging informatics in medicine
The early detection and accurate diagnosis of liver fibrosis, a progressive and potentially serious liver condition, are crucial for effective medical intervention. Invasive methods like biopsies for diagnosis can be risky and expensive. This researc...

Meta-lasso: new insight on infection prediction after minimally invasive surgery.

Medical & biological engineering & computing
Surgical site infection (SSI) after minimally invasive lung cancer surgery constitutes an important factor influencing the direct and indirect economic implications, patient prognosis, and the 5-year survival rate for early-stage lung cancer patients...

The State of Artificial Intelligence in Pediatric Surgery: A Systematic Review.

Journal of pediatric surgery
BACKGROUND: Artificial intelligence (AI) has been recently shown to improve clinical workflows and outcomes - yet its potential in pediatric surgery remains largely unexplored. This systematic review details the use of AI in pediatric surgery.

A Spiking Artificial Vision Architecture Based on Fully Emulating the Human Vision.

Advanced materials (Deerfield Beach, Fla.)
Intelligent vision necessitates the deployment of detectors that are always-on and low-power, mirroring the continuous and uninterrupted responsiveness characteristic of human vision. Nonetheless, contemporary artificial vision systems attain this go...

METnet: A novel deep learning model predicting MET dysregulation in non-small-cell lung cancer on computed tomography images.

Computers in biology and medicine
BACKGROUND: Mesenchymal epithelial transformation (MET) is a key molecular target for diagnosis and treatment of non-small cell lung cancer (NSCLC). The corresponding molecularly targeted therapeutics have been approved by Food and Drug Administratio...

Recent Progress of Protein Tertiary Structure Prediction.

Molecules (Basel, Switzerland)
The prediction of three-dimensional (3D) protein structure from amino acid sequences has stood as a significant challenge in computational and structural bioinformatics for decades. Recently, the widespread integration of artificial intelligence (AI)...