AIMC Topic: Algorithms

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Integrative toxicogenomics: Advancing precision medicine and toxicology through artificial intelligence and OMICs technology.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
More information about a person's genetic makeup, drug response, multi-omics response, and genomic response is now available leading to a gradual shift towards personalized treatment. Additionally, the promotion of non-animal testing has fueled the c...

Artificial Intelligence Algorithms Need to Be Explainable-or Do They?

Journal of nuclear medicine : official publication, Society of Nuclear Medicine

Machine learning-based detection and mapping of riverine litter utilizing Sentinel-2 imagery.

Environmental science and pollution research international
Despite the substantial impact of rivers on the global marine litter problem, riverine litter has been accorded inadequate consideration. Therefore, our objective was to detect riverine litter by utilizing middle-scale multispectral satellite images ...

Can Machine Learning Be Better than Biased Readers?

Tomography (Ann Arbor, Mich.)
Training machine learning (ML) models in medical imaging requires large amounts of labeled data. To minimize labeling workload, it is common to divide training data among multiple readers for separate annotation without consensus and then combine th...

A Hybrid Multimodal Emotion Recognition Framework for UX Evaluation Using Generalized Mixture Functions.

Sensors (Basel, Switzerland)
Multimodal emotion recognition has gained much traction in the field of affective computing, human-computer interaction (HCI), artificial intelligence (AI), and user experience (UX). There is growing demand to automate analysis of user emotion toward...

Flamingo-Optimization-Based Deep Convolutional Neural Network for IoT-Based Arrhythmia Classification.

Sensors (Basel, Switzerland)
Cardiac arrhythmia is a deadly disease that threatens the lives of millions of people, which shows the need for earlier detection and classification. An abnormal signal in the heart causing arrhythmia can be detected at an earlier stage when the heal...

Predicting drug adverse effects using a new Gastro-Intestinal Pacemaker Activity Drug Database (GIPADD).

Scientific reports
Electrical data could be a new source of big-data for training artificial intelligence (AI) for drug discovery. A Gastro-Intestinal Pacemaker Activity Drug Database (GIPADD) was built using a standardized methodology to test drug effects on electrica...

Use of machine learning as a tool for determining fire management units in the brazilian atlantic forest.

Anais da Academia Brasileira de Ciencias
Geoprocessing techniques are generally applied in natural disaster risk management due to their ability to integrate and visualize different sets of geographic data. The objective of this study was to evaluate the capacity of classification and regre...

The long path ahead of robotics in psychiatry.

European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology

Explainability and white box in drug discovery.

Chemical biology & drug design
Recently, artificial intelligence (AI) techniques have been increasingly used to overcome the challenges in drug discovery. Although traditional AI techniques generally have high accuracy rates, there may be difficulties in explaining the decision pr...