AIMC Topic: Humans

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Design of Deep Learning Model for Task-Evoked fMRI Data Classification.

Computational intelligence and neuroscience
Machine learning methods have been successfully applied to neuroimaging signals, one of which is to decode specific task states from functional magnetic resonance imaging (fMRI) data. In this paper, we propose a model that simultaneously utilizes cha...

Analysis of Sports Performance Prediction Model Based on GA-BP Neural Network Algorithm.

Computational intelligence and neuroscience
There are many factors that affect athletes' sports performance in sports competitions. The traditional sports performance prediction method is difficult to obtain more accurate sports performance prediction results and corresponding data analysis in...

Radiomics machine learning study with a small sample size: Single random training-test set split may lead to unreliable results.

PloS one
This study aims to determine how randomly splitting a dataset into training and test sets affects the estimated performance of a machine learning model and its gap from the test performance under different conditions, using real-world brain tumor rad...

A case of fatal multidrug intoxication involving flualprazolam: distribution in body fluids and solid tissues.

Forensic toxicology
PURPOSE: Designer benzodiazepines (DBZDs) increasingly emerged on the novel psychoactive substance (NPS) market in the last few years. They are usually sold as readily available alternatives to prescription benzodiazepines (BZDs) or added to counterf...

Fast and Accurate Ophthalmic Medication Bottle Identification Using Deep Learning on a Smartphone Device.

Ophthalmology. Glaucoma
PURPOSE: To assess the accuracy and efficacy of deep learning models, specifically convolutional neural networks (CNNs), to identify glaucoma medication bottles.

Mammographic Surveillance After Breast-Conserving Therapy: Impact of Digital Breast Tomosynthesis and Artificial Intelligence-Based Computer-Aided Detection.

AJR. American journal of roentgenology
Postoperative mammograms present interpretive challenges due to postoperative distortion and hematomas. The application of digital breast tomosyn-thesis (DBT) and artificial intelligence-based computer-aided detection (AI-CAD) after breast-conservin...

Clinical implementation of deep-learning based auto-contouring tools-Experience of three French radiotherapy centers.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Deep-learning (DL)-based auto-contouring solutions have recently been proposed as a convincing alternative to decrease workload of target volumes and organs-at-risk (OAR) delineation in radiotherapy planning and improve inter-observer consistency. Ho...

AI models and the future of genomic research and medicine: True sons of knowledge?: Artificial intelligence needs to be integrated with causal conceptions in biomedicine to harness its societal benefits for the field.

BioEssays : news and reviews in molecular, cellular and developmental biology
The increasing availability of large-scale, complex data has made research into how human genomes determine physiology in health and disease, as well as its application to drug development and medicine, an attractive field for artificial intelligence...

External Validation of Deep Learning Algorithm for Detecting and Visualizing Femoral Neck Fracture Including Displaced and Non-displaced Fracture on Plain X-ray.

Journal of digital imaging
This study aimed to develop a method for detection of femoral neck fracture (FNF) including displaced and non-displaced fractures using convolutional neural network (CNN) with plain X-ray and to validate its use across hospitals through internal and ...