AIMC Topic: Algorithms

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Artificial intelligence for natural product drug discovery.

Nature reviews. Drug discovery
Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have le...

A scalable second order optimizer with an adaptive trust region for neural networks.

Neural networks : the official journal of the International Neural Network Society
We introduce Tadam (Trust region ADAptive Moment estimation), a new optimizer based on the trust region of the second-order approximation of the loss using the Fisher information matrix. Despite the enhanced gradient estimations offered by second-ord...

Advocating for neurodata privacy and neurotechnology regulation.

Nature protocols
The ability to record and alter brain activity by using implantable and nonimplantable neural devices, while poised to have significant scientific and clinical benefits, also raises complex ethical concerns. In this Perspective, we raise awareness of...

Learning heterogeneous delays in a layer of spiking neurons for fast motion detection.

Biological cybernetics
The precise timing of spikes emitted by neurons plays a crucial role in shaping the response of efferent biological neurons. This temporal dimension of neural activity holds significant importance in understanding information processing in neurobiolo...

An interpretable deep learning framework for predicting liver metastases in postoperative colorectal cancer patients using natural language processing and clinical data integration.

Cancer medicine
BACKGROUND: The significance of liver metastasis (LM) in increasing the risk of death for postoperative colorectal cancer (CRC) patients necessitates innovative approaches to predict LM.

Performance evaluation of deep learning models for the classification and identification of dental implants.

The Journal of prosthetic dentistry
STATEMENT OF PROBLEM: Dental implant systems can be identified using image classification deep learning. However, investigations on the accuracy of classifying and identifying implant design through an object detection model are lacking.

Artificial neural network-based shelf life prediction approach in the food storage process: A review.

Critical reviews in food science and nutrition
The prediction of food shelf life has become a vital tool for distributors and consumers, enabling them to determine storage and optimal edible time, thus avoiding unexpected food waste. Artificial neural network (ANN) have emerged as an effective, f...

Low-dose liver CT: image quality and diagnostic accuracy of deep learning image reconstruction algorithm.

European radiology
OBJECTIVES: To perform a comprehensive within-subject image quality analysis of abdominal CT examinations reconstructed with DLIR and to evaluate diagnostic accuracy compared to the routinely applied adaptive statistical iterative reconstruction (ASi...

Protein classification by autofluorescence spectral shape analysis using machine learning.

Talanta
Depending on the relative numbers and spatial arrangement of Tryptophan (Trp; W) and Tyrosine (Tyr; Y) residues, different proteins produce distinct autofluorescence (AF) spectral shapes when excited at ∼280 nm. Yet, considering the vast number and h...

Symmetric LINEX loss twin support vector machine for robust classification and its fast iterative algorithm.

Neural networks : the official journal of the International Neural Network Society
Twin support vector machine (TSVM) is a practical machine learning algorithm, whereas traditional TSVM can be limited for data with outliers or noises. To address this problem, we propose a novel TSVM with the symmetric LINEX loss function (SLTSVM) f...