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Comparison of pharmacist evaluation of medication orders with predictions of a machine learning model
Sophie-CamilleHogue, FloraChen, GenevièveBrassard....
Published date-11/03/2020
The objective of this work was to assess the clinical performance of an unsupervised machine learning model aimed at identifying unusual medication orders and pharmacological profiles. We conducted a prospective …
CMT in TREC-COVID Round 2: Mitigating the Generalization Gaps from Web to Special Domain Search
ChenyanXiong, ZhenghaoLiu, SiSun....
Published date-11/03/2020
DomainAdaptation, Few-ShotLearning, InformationRetrieval
Neural rankers based on deep pretrained language models (LMs) have been shown to improve many information retrieval benchmarks. However, these methods are affected by their the correlation between pretraining domain …
Generalization to New Actions in Reinforcement Learning
AyushJain, AndrewSzot, JosephJ.Lim....
Published date-11/03/2020
A fundamental trait of intelligence is the ability to achieve goals in the face of novel circumstances, such as making decisions from new action choices. However, standard reinforcement learning assumes …
Brain Predictability toolbox: a Python library for neuroimaging based machine learning
SageHahn, DekangYuan, WesleyThompson....
Published date-11/03/2020
Summary Brain Predictability toolbox (BPt) represents a unified framework of machine learning (ML) tools designed to work with both tabulated data (in particular brain, psychiatric, behavioral, and physiological variables) and …
VEGA: Towards an End-to-End Configurable AutoML Pipeline
BochaoWang, HangXu, JiajinZhang....
Published date-11/03/2020
AutoML, DataAugmentation, HyperparameterOptimization, ModelCompression, NeuralArchitectureSearch
Automated Machine Learning (AutoML) is an important industrial solution for automatic discovery and deployment of the machine learning models. However, designing an integrated AutoML system faces four great challenges of …
Improved unsupervised physics-informed deep learning for intravoxel-incoherent motion modeling and evaluation in pancreatic cancer patients
MishaP.T.Kaandorp, SebastianoBarbieri, RemyKlaassen....
Published date-11/03/2020
${\bf Purpose}$: Earlier work showed that IVIM-NET$_{orig}$, an unsupervised physics-informed deep neural network, was faster and more accurate than other state-of-the-art intravoxel-incoherent motion (IVIM) fitting approaches to DWI. This study …