AIMC Topic: Humans

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Diabetic retinopathy screening through artificial intelligence algorithms: A systematic review.

Survey of ophthalmology
Diabetic retinopathy (DR) poses a significant challenge in diabetes management, with its progression often asymptomatic until advanced stages. This underscores the urgent need for cost-effective and reliable screening methods. Consequently, the integ...

Predictive model for assessing malnutrition in elderly hospitalized cancer patients: A machine learning approach.

Geriatric nursing (New York, N.Y.)
BACKGROUND: Malnutrition is prevalent among elderly cancer patients. This study aims to develop a predictive model for malnutrition in hospitalized elderly cancer patients.

Predicting Dental General Anesthesia Use among Children with Behavioral Health Conditions.

JDR clinical and translational research
OBJECTIVES: To evaluate how different data sources affect the performance of machine learning algorithms that predict dental general anesthesia use among children with behavioral health conditions.

A Data-Driven Approach to Predicting Recreational Activity Participation Using Machine Learning.

Research quarterly for exercise and sport
With the popularity of recreational activities, the study aimed to develop prediction models for recreational activity participation and explore the key factors affecting participation in recreational activities. A total of 12,712 participants, exc...

RDLR: A Robust Deep Learning-Based Image Registration Method for Pediatric Retinal Images.

Journal of imaging informatics in medicine
Retinal diseases stand as a primary cause of childhood blindness. Analyzing the progression of these diseases requires close attention to lesion morphology and spatial information. Standard image registration methods fail to accurately reconstruct pe...

Analysis of convolutional neural networks for fronto-temporal dementia biomarker discovery.

International journal of computer assisted radiology and surgery
PURPOSE: Frontotemporal lobe dementia (FTD) results from the degeneration of the frontal and temporal lobes. It can manifest in several different ways, leading to the definition of variants characterised by their distinctive symptomatologies. As thes...

Multi-label classification of retinal diseases based on fundus images using Resnet and Transformer.

Medical & biological engineering & computing
Retinal disorders are a major cause of irreversible vision loss, which can be mitigated through accurate and early diagnosis. Conventionally, fundus images are used as the gold diagnosis standard in detecting retinal diseases. In recent years, more a...

A topological description of loss surfaces based on Betti Numbers.

Neural networks : the official journal of the International Neural Network Society
In the context of deep learning models, attention has recently been paid to studying the surface of the loss function in order to better understand training with methods based on gradient descent. This search for an appropriate description, both anal...

FDAA: A feature distribution-aware transferable adversarial attack method.

Neural networks : the official journal of the International Neural Network Society
In recent years, the research on transferable feature-level adversarial attack has become a hot spot due to attacking unknown deep neural networks successfully. But the following problems limit its transferability. Existing feature disruption methods...

GRAM: An interpretable approach for graph anomaly detection using gradient attention maps.

Neural networks : the official journal of the International Neural Network Society
Detecting unusual patterns in graph data is a crucial task in data mining. However, existing methods face challenges in consistently achieving satisfactory performance and often lack interpretability, which hinders our understanding of anomaly detect...