MachineLearning相关论文
Machine learning algorithm as a prognostic tool for Epstein-Barr virus reactivation after haploident
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Machine Learning-Based Scoring System for Early Prognosis Evaluation of Patients with Coronavirus Di
Background:Theglobalspreadofcoronavirusdisease2019(COVID-19)continuestothreatenhumanhealthsecurity,exertingconsiderablep......
Machine learning approach for label-free rapid detection and identification of virus using Raman spe
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Single-molecule detection and imaging are of great value in chemical analysis,biomarker identification and other trace d......
目的:探讨结合患者临床信息和CT特征构建的基于机器学习的非参数诊断模型判定多发肺结节中实性结节性质的效力。方法:回顾性收集北......
In the recent years, a dramatic boost of the research is observed at the junction of photonics, machine learning and art......
Organic rich laminated shale is one type of favorable reservoirs for exploration and development of continental shale oi......
Seismic reservoir prediction plays an important role in oil exploration and development.With the progress of artificial ......
Adversarial Malware Example (AME)-based adversarial training can effectively enhance the robustness of Machine Learning ......
Artificial intelligence(AI)is a general term that refers to the use of a machine to imitate intelligent behavior for per......
Automatic seizure detection with different time delays using SDFT and time-domain feature extraction
Automatic seizure detection is important for fast detection of the seizure because the way that the expert denotes and s......
The development of phononic crystals,especially their interaction with topological insulators,allows exploration of the ......
Soil spatial information has traditionally been presented as polygon maps at coarse scales.Solving global and local issu......
泰德·安德伍德是伊利诺伊大学厄巴纳—香槟分校英文系和信息科学学院的教授.近十年来,在应对“数字”与“人文”之间日趋激烈的对......
Theoretical predictions on α-decay properties of some unknown neutron-deficient actinide nuclei usin
Neutron-deficient actinide nuclei provide a valuable window to probe heavy nuclear systems with large proton-neutron rat......
This study has provided an approach to classify soil using machine learning.Multiclass elements of stand-alone machine l......
Alloys designed with the traditional trial and error method have encountered several problems, such as long trial cycles......
Evaluating data-driven algorithms for predicting mechanical properties with small datasets: A case s
Data-driven algorithms for predicting mechanical properties with small datasets are evaluated in a case study on gear st......
Background: Tension pneumothorax is one of the leading causes of preventable death on the battlefield. Current prehospit......
In some studies on landslide susceptibility mapping(LSM),landslide boundary and spatial shape charac-teristics have been......
In the past decades, there have been numerous advancements in the field of technology. This has led to many scientific b......
In multi-dimensional classification(MDC),the semantics of objects are characterized by multiple class spaces from differ......
Multi-Distributed Speech Emotion Recognition Based on Mel Frequency Cepstogram and Parameter Transfe
Speech emotion recognition(SER)is the use of speech signals to estimate the state of emotion.At present,machine learning......
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As vehicle complexity and road congestion increase,combined with the emergence of electric vehicles,the need for intelli......
机器学习构建预测模型可以早期预测重症患者急性肾损伤（AKI），有助于临床尽早采取预防措施以降低AKI的发生率。机器学习也可以做到实时......
Characterization of the Convoluted 3D Intermetallic Phases in a Recycled Al Alloy by Synchrotron X-r
Fe-rich intermetallic phases in recycled Al alloys often exhibit complex and 3D convoluted structures and morphologies.T......
Computational mesh is an important ingredient that affects the accuracy and efficiency of CFD numerical simulation.In li......
Rapidly identifying protein complexes is signifi-cant to elucidate the mechanisms of macromolecular interac-tions and to......
Electronic devices require the printed circuit board(PCB) to support the whole structure,but the assembly of PCBs suffer......
Using machine learning models to explore the solution space of large nonlinear systems underlying fl
Flowsheet simulations of chemical processes on an industrial scale require the solution of large systems of nonlinear eq......
Studying the complex quantum dynamics of interacting many-body systems is one of the most challeng-ing areas in modern p......
Premenstrual dysphoric disorder (PMDD) affects nearly 5％ of women of reproductive age.Symptomatic heterogeneity,together ......
Drug repurposing for cancer treatment through global propagation with a greedy algorithm in a multil
Objective: Drug repurposing, the application of existing therapeutics to new indications, holds promise in achieving rap......
Monte Carlo (MC) methods are important computational tools for molecular struc-ture optimizations and predictions.When s......
Efficient Selection of Linearly Independent Atomic Features for Accurate Machine Learning Potentials
Machine learning potentials are promising in atomistic sim-ulations due to their compara-ble accuracy to first-principle......
中国山区多、地形复杂,构造发育、地质灾害隐患分布广泛.滑坡作为山区最具灾难性的地质灾害之一,严重威胁着人民群众的生命及财产......
Machine learning and numerical investigation on drag reduction of underwater serial multi-projectile
To increase launching frequency and decrease drag force of underwater projectiles,a serial multi-projectiles structure b......
SPONGE (Simulation Package tOward Next GEneration molecular modeling) is a software package for molecu-lar dynamics (MD)......
Nowcasts of strong convective precipitation and radar-based quantitative precipitation estimations have always been hot ......
Many high quality studies have emerged from public databases,such as Surveillance,Epidemiology,and End Results(SEER),Nat......
Timely and reliable estimation of regional crop yield is a vital component of food security assessment, especially in de......
We study the non-Markovian dynamics of an open quantum system with machine learning.The observable physical quantities a......
Design Methods and Strategies for Forward and Inverse Problems of Turbine Blades Based on Machine Le
To study the feasibility of using machine learning technology to solve the forward problem (prediction of aerodynamic pa......
Feline animals can run quickly using spinal joints as well as the joints that make up their four legs.This paper describ......
随着能源需求增长与化石燃料资源枯竭之间的矛盾日益突出,以及石油、天然气等不可再生资源的燃烧带来的环境问题和全球变暖,清洁可......
Recent Advances in Data-Driven Wireless Communication Using Gaussian Processes:A Comprehensive Surve
Data-driven paradigms are well-known and salient demands of future wireless communication.Em-powered by big data and mac......
