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Machine Learning Prediction of Clinical Trial Operational Efficiency.

The AAPS journal
Clinical trials are the gatekeepers and bottlenecks of progress in medicine. In recent years, they have become increasingly complex and expensive, driven by a growing number of stakeholders requiring more endpoints, more diverse patient populations, ...

Artificial intelligence in gastrointestinal and hepatic imaging: past, present and future scopes.

Clinical imaging
The use of technology in medicine has grown exponentially because of the technological advancements allowing the digitization of medical data and optimization of their processing to extract multiple features of significant clinical relevance. Radiolo...

Prediction of Purchase Volume of Cross-Border e-Commerce Platform Based on BP Neural Network.

Computational intelligence and neuroscience
As a new form of foreign trade, cross-border e-commerce has huge development potential. Although the development prospect of cross-border e-commerce is good, the management of global supply chain is very important in order to gain a place in the fier...

A Novel Encoder-Decoder Model for Multivariate Time Series Forecasting.

Computational intelligence and neuroscience
The time series is a kind of complex structure data, which contains some special characteristics such as high dimension, dynamic, and high noise. Moreover, multivariate time series (MTS) has become a crucial study in data mining. The MTS utilizes the...

Multimodal molecular imaging in drug discovery and development.

Drug discovery today
In addition to individual imaging techniques, the combination and integration of several imaging techniques, so-called multimodal imaging, can provide large amounts of anatomical, functional, and molecular information accelerating drug discovery and ...

Artificial intelligence in prostate cancer: Definitions, current research, and future directions.

Urologic oncology
Multiple novel modalities tasking artificial intelligence based computational pathology applications and integrating other variables, such as risk factors, tumor microenvironment, genomic testing data, laboratory findings, clinical history, and radio...

Deep learning time series prediction models in surveillance data of hepatitis incidence in China.

PloS one
BACKGROUND: Precise incidence prediction of Hepatitis infectious disease is critical for early prevention and better government strategic planning. In this paper, we presented different prediction models using deep learning methods based on the month...

[Artificial intelligence: a solution for the lack of pathologists?].

Der Pathologe
Given the rapid developments, there is no doubt that artificial intelligence (AI) will substantially impact pathological diagnostics. However, it remains an open question if AI will primarily be another diagnostic tool, such as immunohistochemistry, ...

Interval type-2 fuzzy computational model for real time Kalman filtering and forecasting of the dynamic spreading behavior of novel Coronavirus 2019.

ISA transactions
This paper presents a computational model based on interval type-2 fuzzy systems for analysis and forecasting of COVID-19 dynamic spreading behavior. The proposed methodology is related to interval type-2 fuzzy Kalman filters design from experimental...

Prediction for Origin-Destination Distribution of Dockless Shared Bicycles: A Case Study in Nanjing City.

Frontiers in public health
Shared bicycles are currently widely welcomed by the public due to their flexibility and convenience; they also help reduce chemical emissions and improve public health by encouraging people to engage in physical activities. However, during their dev...