Results 101 to 110 of about 9,899,096 (370)
Learning Task-aware Robust Deep Learning Systems [PDF]
arXiv, 2020 Many works demonstrate that deep learning system is vulnerable to adversarial attack. A deep learning system consists of two parts: the deep learning task and the deep model. Nowadays, most existing works investigate the impact of the deep model on robustness of deep learning systems, ignoring the impact of the learning task.
arxiv
Molecular Oncology, EarlyView.Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran +16 more
wiley +1 more source
Non-Zero Crossing Point Detection in a Distorted Sinusoidal Signal Using Logistic Regression Model
Computers, 2022 Non-Zero crossing point detection in a sinusoidal signal is essential in case of various power system and power electronics applications like power system protection and power converters controller design.
Venkataramana Veeramsetty +2 more
doaj +1 more source
Deep Learning in the Field of Biometric Template Protection: An Overview [PDF]
arXiv, 2023 Today, deep learning represents the most popular and successful form of machine learning. Deep learning has revolutionised the field of pattern recognition, including biometric recognition. Biometric systems utilising deep learning have been shown to achieve auspicious recognition accuracy, surpassing human performance.
arxiv
Molecular Oncology, EarlyView.Prostate cancer is a leading malignancy with significant clinical heterogeneity in men. An 11‐gene signature derived from dysregulated epithelial cell markers effectively predicted biochemical recurrence‐free survival in patients who underwent radical surgery or radiotherapy.
Zhuofan Mou, Lorna W. Harries
wiley +1 more source
Deep learning for supervised classification [PDF]
, 2016 One of the most recent area in the Machine Learning research is Deep Learning. Deep Learning algorithms have been applied successfully to computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics ...
DI CIACCIO, AGOSTINO +1 more
core
Alzheimer’s Research & TherapyBackground The use of polygenic risk scores (PRS) for predicting disease risk in Japanese populations, particularly for dementia and related phenotypes, remains markedly unexplored.
Misato Kaishima +6 more
doaj +1 more source
A Classifier Based on K-Nearest Neighbors Using Weighted Summation of Reconstruction Errors [PDF]
مجله مدل سازی در مهندسیIn this paper, a classifier is introduced based on the nearest neighbor classifier and the reconstruction error for data classification. In the proposed method, first, K nearest data points (neighbors) from each category in the training data are ...
Rassoul Hajizadeh +1 more
doaj +1 more source
Exploration of heterogeneity and recurrence signatures in hepatocellular carcinoma
Molecular Oncology, EarlyView.This study leveraged public datasets and integrative bioinformatic analysis to dissect malignant cell heterogeneity between relapsed and primary HCC, focusing on intercellular communication, differentiation status, metabolic activity, and transcriptomic profiles.
Wen‐Jing Wu +15 more
wiley +1 more source
Molecular Oncology, EarlyView.This article advocates integrating temporal dynamics into cancer research. Rather than relying on static snapshots, researchers should increasingly consider adopting dynamic methods—such as live imaging, temporal omics, and liquid biopsies—to track how tumors evolve over time.
Gautier Follain +3 more
wiley +1 more source