Toward human intervention-free clinical diagnosis of intracranial aneurysm via deep neural network [0.03%]
基于深度神经网络的无须人工干预的颅内动脉瘤临床诊断方法研究
Zi-Hao Bo,Hui Qiao,Chong Tian et al.
Zi-Hao Bo et al.
Intracranial aneurysm (IA) is an enormous threat to human health, which often results in nontraumatic subarachnoid hemorrhage or dismal prognosis. Diagnosing IAs on commonly used computed tomographic angiography (CTA) examinations remains l...
An interpretable deep-learning model for early prediction of sepsis in the emergency department [0.03%]
一种可解释的深度学习模型 用于急诊科早期预测脓毒症
Dongdong Zhang,Changchang Yin,Katherine M Hunold et al.
Dongdong Zhang et al.
Sepsis is a life-threatening condition with high mortality rates and expensive treatment costs. Early prediction of sepsis improves survival in septic patients. In this paper, we report our top-performing method in the 2019 DII National Dat...
Topic classification of electric vehicle consumer experiences with transformer-based deep learning [0.03%]
基于变压器的深度学习的电动汽车消费者体验话题分类
Sooji Ha,Daniel J Marchetto,Sameer Dharur et al.
Sooji Ha et al.
The transportation sector is a major contributor to greenhouse gas (GHG) emissions and is a driver of adverse health effects globally. Increasingly, government policies have promoted the adoption of electric vehicles (EVs) as a solution to ...
Decontextualized learning for interpretable hierarchical representations of visual patterns [0.03%]
去情境化学习：用于解释性层次视觉模式表征的方法
Robert Ian Etheredge,Manfred Schartl,Alex Jordan
Robert Ian Etheredge
Apart from discriminative modeling, the application of deep convolutional neural networks to basic research utilizing natural imaging data faces unique hurdles. Here, we present decontextualized hierarchical representation learning (DHRL), ...
Ye Wei,Rama Srinivas Varanasi,Torsten Schwarz et al.
Ye Wei et al.
Mass spectrometry is a widespread approach used to work out what the constituents of a material are. Atoms and molecules are removed from the material and collected, and subsequently, a critical step is to infer their correct identities bas...
Machine learning for guiding high-temperature PEM fuel cells with greater power density [0.03%]
基于机器学习的高功率密度高温型质子交换膜燃料电池引导技术
Luis A Briceno-Mena,Gokul Venugopalan,José A Romagnoli et al.
Luis A Briceno-Mena et al.
High-temperature polymer electrolyte membrane fuel cells (HT-PEMFCs) are enticing energy conversion technologies because they use low-cost hydrogen generated from methane and have simple water and heat management. However, proliferation of ...
A comprehensive survey on smart contract construction and execution: paradigms, tools, and systems [0.03%]
面向智能合约构造与执行的综合调查：范式、工具和系统
Bin Hu,Zongyang Zhang,Jianwei Liu et al.
Bin Hu et al.
Smart contracts are regarded as one of the most promising and appealing notions in blockchain technology. Their self-enforcing and event-driven features make some online activities possible without a trusted third party. Nevertheless, probl...
Uncovering social-contextual and individual mental health factors associated with violence via computational inference [0.03%]
基于计算推理的暴力行为相关社会因素和个体心理健康因素分析
Hernando Santamaría-García,Sandra Baez,Diego Mauricio Aponte-Canencio et al.
Hernando Santamaría-García et al.
The identification of human violence determinants has sparked multiple questions from different academic fields. Innovative methodological assessments of the weight and interaction of multiple determinants are still required. Here, we exami...
How Could COVID-19 Change Scholarly Communication to a New Normal in the Open Science Paradigm? [0.03%]
新冠疫情如何使学术交流转变为开放科学的新常态？
Kazuhiro Hayashi
Kazuhiro Hayashi
Author reviews digital transformation of scholarly communication since 1990s and explains how COVID-19 is accelerating open science, with some analogy of chemical reactions. Discussing the current situation of preprint, the potential of pee...
How Do Data Bolster Pandemic Preparedness and Response? How Do We Improve Data and Systems to Be Better Prepared? [0.03%]
数据如何助力大流行病的防范和应对？我们又该如何改进数据和系统以更好地应对突发情况？
Priyanka Pillai
Priyanka Pillai
How are data driving the response for the ongoing COVID-19 pandemic? How do data support preparedness toward epidemics and pandemics? How do data inform the potential severity and spread of an outbreak? Past infectious disease outbreaks hav...