Data integration challenges for machine learning in precision medicine
M Martínez-García, E Hernández-Lemus - Frontiers in medicine, 2022 - frontiersin.org
A main goal of Precision Medicine is that of incorporating and integrating the vast corpora on
different databases about the molecular and environmental origins of disease, into analytic …
different databases about the molecular and environmental origins of disease, into analytic …
[HTML][HTML] Predicting gene and protein expression levels from DNA and protein sequences with Perceiver
Abstract Background and Objective. The functions of an organism and its biological
processes result from the expression of genes and proteins. Therefore quantifying and …
processes result from the expression of genes and proteins. Therefore quantifying and …
HPC Platform for Railway Safety-Critical Functionalities Based on Artificial Intelligence
M Labayen, L Medina, F Eizaguirre, J Flich… - Applied Sciences, 2023 - mdpi.com
The automation of railroad operations is a rapidly growing industry. In 2023, a new
European standard for the automated Grade of Automation (GoA) 2 over European Train …
European standard for the automated Grade of Automation (GoA) 2 over European Train …
A deep analysis on high‐resolution dermoscopic image classification
Convolutional neural networks (CNNs) have been broadly employed in dermoscopic image
analysis, mainly as a result of the large amount of data gathered by the International Skin …
analysis, mainly as a result of the large amount of data gathered by the International Skin …
Convolutional Neural Network Model for Segmentation and Classification of Clear Cell Renal Cell Carcinoma Based on Multiphase CT Images
VO Bolocan, M Secareanu, E Sava, C Medar… - Journal of …, 2023 - mdpi.com
(1) Background: Computed tomography (CT) imaging challenges in diagnosing renal cell
carcinoma (RCC) include distinguishing malignant from benign tissues and determining the …
carcinoma (RCC) include distinguishing malignant from benign tissues and determining the …
Enhancing open-vocabulary semantic segmentation with prototype retrieval
Large-scale pre-trained vision-language models like CLIP exhibit impressive zero-shot
capabilities in classification and retrieval tasks. However, their application to open …
capabilities in classification and retrieval tasks. However, their application to open …
AI support for accelerating histopathological slide examinations of prostate cancer in clinical studies
While studies in pathology are essential for the progress in the diagnostic and prognostic
techniques in the field, pathologist time is becoming an increasingly scarce resource, and …
techniques in the field, pathologist time is becoming an increasingly scarce resource, and …
Lung nodules segmentation with deephealth toolkit
The accurate and consistent border segmentation plays an important role in the tumor
volume estimation and its treatment in the field of Medical Image Segmentation. Globally …
volume estimation and its treatment in the field of Medical Image Segmentation. Globally …
VSA: A hybrid vector-systolic architecture
MV Maceiras, MW Azhar… - 2022 IEEE 40th …, 2022 - ieeexplore.ieee.org
In order to deliver high performance efficiently, modern processors include dedicated
hardware to accelerate different application domains. For example, several recent …
hardware to accelerate different application domains. For example, several recent …
Efficient inference of image-based neural network models in reconfigurable systems with pruning and quantization
Neural networks (NN) for image processing in embedded systems expose two conflicting
requirements: increasing computing power needs as models become more complex and …
requirements: increasing computing power needs as models become more complex and …