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Mostrando ítems 1-10 de 34
Artículo
Dual Machine-Learning system to aid Glaucoma Diagnosis using disc and cup feature extraction.
(IEEE Computer Society, 2020)
Glaucoma is a degenerative disease that affects vision, causing damage to the optic nerve that ends in vision loss. The classic techniques to detect it have undergone a great change since the intrusion of machine learning ...
Artículo
Non-small cell lung cancer diagnosis aid with histopathological images using Explainable Deep Learning techniques
(Elsevier, 2022-11)
Background: Lung cancer has the highest mortality rate in the world, twice as high as the second highest. On the other hand, pathologists are overworked and this is detrimental to the time spent on each patient, diagnostic ...
Ponencia
Multidataset Incremental Training for Optic Disc Segmentation
(Springer, 2020)
When convolutional neural networks are applied to image segmentation results depend greatly on the data sets used to train the networks. Cloud providers support multi GPU and TPU virtual machines making the idea of ...
Artículo
AnkFall—Falls, Falling Risks and Daily-Life Activities Dataset with an Ankle-Placed Accelerometer and Training Using Recurrent Neural Networks
(MDPI, 2021)
Falls are one of the leading causes of permanent injury and/or disability among the elderly. When these people live alone, it is convenient that a caregiver or family member visits them periodically. However, these visits ...
Capítulo de Libro
Perspective Chapter: Internet of Things in Healthcare: New Trends, Challenges and Hurdles
(IntechOpen, 2022-08)
Applied to health field, Internet of Things (IoT) systems provides continuous and ubiquitous monitoring and assistance, allowing the creation of valuable tools for diag nosis, health empowerment, and personalized treatment, ...
Artículo
A study on the use of Edge TPUs for eye fundus image segmentation
(Elsevier, 2021)
Medical image segmentation can be implemented using Deep Learning methods with fast and efficient segmentation networks. Single-board computers (SBCs) are difficult to use to train deep networks due to their memory and ...
Artículo
Does Two-Class Training Extract Real Features? A COVID-19 Case Study
(MDPI, 2021-01)
Diagnosis aid systems that use image analysis are currently very useful due to the large workload of health professionals involved in making diagnoses. In recent years, Convolutional Neural Networks (CNNs) have been used ...
Ponencia
Glioma Diagnosis Aid through CNNs and Fuzzy-C Means for MRI
(ScitePress Digital Library, 2019)
Glioma is a type of brain tumor that causes mortality in many cases. Early diagnosis is an important factor. Typically, it is detected through MRI and then either a treatment is applied, or it is removed through ...
Capítulo de Libro
Sistema lumínico para la medición de la reacción motora
(3ciencias, 2022-02-03)
El mundo del deporte ha sufrido un gran cambio, llevando al extremo las exigencias físicas de los deportistas. Uno de los aspectos más importantes en deportes de velocidad es la respuesta de reacción del deportista ante ...
Artículo
A lightweight xAI approach to cervical cancer classification
(Springer, 2024-03)
Cervical cancer is caused in the vast majority of cases by the human papilloma virus (HPV) through sexual contact and requires a specific molecular-based analysis to be detected. As an HPV vaccine is available, the incidence ...