AI Medical Compendium Topic:
Time Factors

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Personalized prediction of daily eczema severity scores using a mechanistic machine learning model.

Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology
BACKGROUND: Atopic dermatitis (AD) is a chronic inflammatory skin disease with periods of flares and remission. Designing personalized treatment strategies for AD is challenging, given the apparent unpredictability and large variation in AD symptoms ...

Real-World Implications of a Rapidly Responsive COVID-19 Spread Model with Time-Dependent Parameters via Deep Learning: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: The COVID-19 pandemic has caused major disruptions worldwide since March 2020. The experience of the 1918 influenza pandemic demonstrated that decreases in the infection rates of COVID-19 do not guarantee continuity of the trend.

Transcervical (SP) and Transhiatal DaVinci Robotic Esophagectomy: A Cadaveric Study.

The Thoracic and cardiovascular surgeon
BACKGROUND: This is a preclinical cadaveric study to investigate the feasibility of a fully robotic McKeown esophagectomy in simultaneous rendezvous technique using the DaVinci X for transhiatal dissection and the DaVinci single port (SP) for transce...

Dynamic event-based state estimation for delayed artificial neural networks with multiplicative noises: A gain-scheduled approach.

Neural networks : the official journal of the International Neural Network Society
This study is concerned with the state estimation issue for a kind of delayed artificial neural networks with multiplicative noises. The occurrence of the time delay is in a random way that is modeled by a Bernoulli distributed stochastic variable wh...

Implementation of Artificial Intelligence-Based Clinical Decision Support to Reduce Hospital Readmissions at a Regional Hospital.

Applied clinical informatics
BACKGROUND: Hospital readmissions are a key quality metric, which has been tied to reimbursement. One strategy to reduce readmissions is to direct resources to patients at the highest risk of readmission. This strategy necessitates a robust predictiv...

Deep-Learning Generation of Synthetic Intermediate Projections Improves Lu SPECT Images Reconstructed with Sparsely Acquired Projections.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
The aims of this study were to decrease the Lu-SPECT acquisition time by reducing the number of projections and to circumvent image degradation by adding deep-learning-generated synthesized projections. We constructed a deep convolutional U-net-shap...