AIMC Topic: Algorithms

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ResBiGAAT: Residual Bi-GRU with attention for protein-ligand binding affinity prediction.

Computational biology and chemistry
Protein-ligand interaction plays a crucial role in drug discovery, facilitating efficient drug development and enabling drug repurposing. Several computational algorithms, such as Graph Neural Networks and Convolutional Neural Networks, have been pro...

Performance of deep learning models for response evaluation on whole-body bone scans in prostate cancer.

Annals of nuclear medicine
OBJECTIVE: We aimed to develop deep learning classifiers for assessing therapeutic response on bone scans of patients with prostate cancer.

HeapMS: An Automatic Peak-Picking Pipeline for Targeted Proteomic Data Powered by 2D Heatmap Transformation and Convolutional Neural Networks.

Analytical chemistry
The process of peak picking and quality assessment for multiple reaction monitoring (MRM) data demands significant human effort, especially for signals with low abundance and high interference. Although multiple peak-picking software packages are ava...

Inherently interpretable position-aware convolutional motif kernel networks for biological sequencing data.

Scientific reports
Artificial neural networks show promising performance in detecting correlations within data that are associated with specific outcomes. However, the black-box nature of such models can hinder the knowledge advancement in research fields by obscuring ...

Emerging applications of machine learning in genomic medicine and healthcare.

Critical reviews in clinical laboratory sciences
The integration of artificial intelligence technologies has propelled the progress of clinical and genomic medicine in recent years. The significant increase in computing power has facilitated the ability of artificial intelligence models to analyze ...

Built to Last? Reproducibility and Reusability of Deep Learning Algorithms in Computational Pathology.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Recent progress in computational pathology has been driven by deep learning. While code and data availability are essential to reproduce findings from preceding publications, ensuring a deep learning model's reusability is more challenging. For that,...

Deep learning in endoscopy: the importance of standardisation.

Acta otorhinolaryngologica Italica : organo ufficiale della Societa italiana di otorinolaringologia e chirurgia cervico-facciale

Predicting individual cases of major adolescent psychiatric conditions with artificial intelligence.

Translational psychiatry
Three-quarters of lifetime mental illness occurs by the age of 24, but relatively little is known about how to robustly identify youth at risk to target intervention efforts known to improve outcomes. Barriers to knowledge have included obtaining rob...

IoT-Based Reinforcement Learning Using Probabilistic Model for Determining Extensive Exploration through Computational Intelligence for Next-Generation Techniques.

Computational intelligence and neuroscience
Computing intelligence is built on several learning and optimization techniques. Incorporating cutting-edge learning techniques to balance the interaction between exploitation and exploration is therefore an inspiring field, especially when it is com...