Considerations for a More Ethical Approach to Data in AI: On Data Representation and Infrastructure [0.03%]
关于AI数据伦理的考量：数据表示与基础设施方面的问题
Alice Baird,Björn Schuller
Alice Baird
Data shapes the development of Artificial Intelligence (AI) as we currently know it, and for many years centralized networking infrastructures have dominated both the sourcing and subsequent use of such data. Research suggests that centrali...
Lars Lau Raket
Lars Lau Raket
Background: The characterizing symptom of Alzheimer disease (AD) is cognitive deterioration. While much recent work has focused on defining AD as a biological construct, most patients are still diagnosed, staged, and treated based on their ...
Christian Berghoff,Matthias Neu,Arndt von Twickel
Christian Berghoff
This article deals with the IT security of connectionist artificial intelligence (AI) applications, focusing on threats to integrity, one of the three IT security goals. Such threats are for instance most relevant in prominent AI computer v...
The ADC API: A Web API for the Programmatic Query of the AIRR Data Commons [0.03%]
ADC API：AIRR数据通用体系结构的程序查询的Web API
Scott Christley,Ademar Aguiar,George Blanck et al.
Scott Christley et al.
The Adaptive Immune Receptor Repertoire (AIRR) Community is a research-driven group that is establishing a clear set of community-accepted data and metadata standards; standards-based reference implementation tools; and policies and practic...
Muhammed Mas-Ud Hussain,Mir Imtiaz Mostafiz,S M Farabi Mahmud et al.
Muhammed Mas-Ud Hussain et al.
We address the problem of maintaining the correct answer-sets to a novel query-Conditional Maximizing Range-Sum (C-MaxRS)-for spatial data. Given a set of 2D point objects, possibly with associated weights, the traditional MaxRS problem det...
Kevin Lopez,Samah J Fodeh,Ahmed Allam et al.
Kevin Lopez et al.
Choosing an optimal data fusion technique is essential when performing machine learning with multimodal data. In this study, we examined deep learning-based multimodal fusion techniques for the combined classification of radiological images...
Theory In, Theory Out: The Uses of Social Theory in Machine Learning for Social Science [0.03%]
从理论到实践：社会学理论在社会科学机器学习中的应用与展望
Jason Radford,Kenneth Joseph
Jason Radford
Research at the intersection of machine learning and the social sciences has provided critical new insights into social behavior. At the same time, a variety of issues have been identified with the machine learning models used to analyze so...
Deep Learning Optimizes Data-Driven Representation of Soil Organic Carbon in Earth System Model Over the Conterminous United States [0.03%]
基于深度学习的美国连土地区土壤有机碳数据驱动表征的优化及在地球系统模型中的应用
Feng Tao,Zhenghu Zhou,Yuanyuan Huang et al.
Feng Tao et al.
Soil organic carbon (SOC) is a key component of the global carbon cycle, yet it is not well-represented in Earth system models to accurately predict global carbon dynamics in response to climate change. This novel study integrated deep lear...
Variational Autoencoder Modular Bayesian Networks for Simulation of Heterogeneous Clinical Study Data [0.03%]
异质性临床研究数据的变分自编码模块贝叶斯网络模拟方法
Luise Gootjes-Dreesbach,Meemansa Sood,Akrishta Sahay et al.
Luise Gootjes-Dreesbach et al.
In the area of Big Data, one of the major obstacles for the progress of biomedical research is the existence of data "silos" because legal and ethical constraints often do not allow for sharing sensitive patient data from clinical studies a...
Improving Diagnosis of Depression With XGBOOST Machine Learning Model and a Large Biomarkers Dutch Dataset (n = 11,081) [0.03%]
基于XGBOOST机器学习模型和大规模生物标志物荷兰数据集改进抑郁症诊断(n=11,081)
Amita Sharma,Willem J M I Verbeke
Amita Sharma
Machine Learning has been on the rise and healthcare is no exception to that. In healthcare, mental health is gaining more and more space. The diagnosis of mental disorders is based upon standardized patient interviews with defined set of q...