AIMC Topic: Machine Learning

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A Predictive Model for Determining Patients Not Requiring Prolonged Hospital Length of Stay After Elective Primary Total Hip Arthroplasty.

Anesthesia and analgesia
BACKGROUND: Hospital length of stay (LOS) is an important quality metric for total hip arthroplasty. Accurately predicting LOS is important to expectantly manage bed utilization and other hospital resources. We aimed to develop a predictive model for...

Evaluation of Stein-O'Brien et al.: To See a World in a Grain of Sand-How to Reveal a Common Latent Space through Multiple Platform Omics Data.

Cell systems
One snapshot of the peer review process for "Decomposing Cell Identity for Transfer Learning across Cellular Measurements, Platforms, Tissues, and Species" (Stein-O'Brien et al., 2019).

[Research on algorithms for identifying the severity of acute respiratory distress syndrome patients based on noninvasive parameters].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Acute respiratory distress syndrome (ARDS) is a serious threat to human life and health disease, with acute onset and high mortality. The current diagnosis of the disease depends on blood gas analysis results, while calculating the oxygenation index....

Obstructive sleep apnea syndrome detection based on ballistocardiogram via machine learning approach.

Mathematical biosciences and engineering : MBE
Obstructive sleep apnea (OSA) is a common sleep-related respiratory disease that affects people's health, especially in the elderly. In the traditional PSG-based OSA detection, people's sleep may be disturbed, meanwhile the electrode slices are easil...