AI Medical Compendium Topic:
Forecasting

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Forecast of E-Commerce Transactions Trend Using Integration of Enhanced Whale Optimization Algorithm and Support Vector Machine.

Computational intelligence and neuroscience
E-commerce has become a crucial business model through the Internet around the world. Therefore, its transaction trend forecast can provide important information for the market planning and development in advance. For this purpose, the integrated mod...

Outcome-Oriented Deep Temporal Phenotyping of Disease Progression.

IEEE transactions on bio-medical engineering
Chronic diseases evolve slowly throughout a patient's lifetime creating heterogeneous progression patterns that make clinical outcomes remarkably varied across individual patients. A tool capable of identifying temporal phenotypes based on the patien...

AI MSK clinical applications: spine imaging.

Skeletal radiology
Recent investigations have focused on the clinical application of artificial intelligence (AI) for tasks specifically addressing the musculoskeletal imaging routine. Several AI applications have been dedicated to optimizing the radiology value chain ...

Artificial Intelligence in Chemistry: Current Trends and Future Directions.

Journal of chemical information and modeling
The application of artificial intelligence (AI) to chemistry has grown tremendously in recent years. In this Review, we studied the growth and distribution of AI-related chemistry publications in the last two decades using the CAS Content Collection....

Future minds and a new challenge to anti-natalism.

Bioethics
Some futurists and philosophers have urged that recent developments in biotechnology promise advancements that challenge standard accepted views of human nature, the self, and ethical obligation. Additionally, some have urged that developments in art...

A New Hybrid Forecasting Model Based on SW-LSTM and Wavelet Packet Decomposition: A Case Study of Oil Futures Prices.

Computational intelligence and neuroscience
The crude oil futures prices forecasting is a significant research topic for the management of the energy futures market. In order to optimize the accuracy of energy futures prices prediction, a new hybrid model is established in this paper which com...

The predictive skill of convolutional neural networks models for disease forecasting.

PloS one
In this paper we investigate the utility of one-dimensional convolutional neural network (CNN) models in epidemiological forecasting. Deep learning models, in particular variants of recurrent neural networks (RNNs) have been studied for ILI (Influenz...

Comparing regression modeling strategies for predicting hometime.

BMC medical research methodology
BACKGROUND: Hometime, the total number of days a person is living in the community (not in a healthcare institution) in a defined period of time after a hospitalization, is a patient-centred outcome metric increasingly used in healthcare research. Ho...

Machine learning to advance the prediction, prevention and treatment of eating disorders.

European eating disorders review : the journal of the Eating Disorders Association
Machine learning approaches are just emerging in eating disorders research. Promising early results suggest that such approaches may be a particularly promising and fruitful future direction. However, there are several challenges related to the natur...

A machine learning based exploration of COVID-19 mortality risk.

PloS one
Early prediction of patient mortality risks during a pandemic can decrease mortality by assuring efficient resource allocation and treatment planning. This study aimed to develop and compare prognosis prediction machine learning models based on invas...