BACKGROUND: Estimating the depth of anaesthesia (DoA) is critical in modern anaesthetic practice. Multiple DoA monitors based on electroencephalograms (EEGs) have been widely used for DoA monitoring; however, these monitors may be inaccurate under ce...
BACKGROUND: There are no established accurate models that use machine learning (ML) methods to preoperatively predict immediate remission after transsphenoidal surgery (TSS) in patients diagnosed with histology-positive Cushing's disease (CD).
IMPORTANCE: Exhaled breath is an attractive option for cancer detection. A sensitive and reliable breath test has the potential to greatly facilitate diagnoses and therapeutic monitoring of lung cancer.
Transcription of eukaryotic genomes involves complex alternative processing of RNAs. Sequencing of full-length RNAs using long reads reveals the true complexity of processing. However, the relatively high error rates of long-read sequencing technolog...
OBJECTIVE: To assess the accuracy and reliability of a machine learning (ML) algorithm for predicting the full audiograms of hearing-impaired children relative to the common approach (CA).
Interdisciplinary sciences, computational life sciences
Feb 27, 2021
Computed tomography (CT) is one of the most efficient diagnostic methods for rapid diagnosis of the widespread COVID-19. However, reading CT films brings a lot of concentration and time for doctors. Therefore, it is necessary to develop an automatic ...
Annals of the New York Academy of Sciences
Feb 26, 2021
We trained a deep learning algorithm to use skin optical coherence tomography (OCT) angiograms to differentiate between healthy and type 2 diabetic mice. OCT angiograms were acquired with a custom-built OCT system based on an akinetic swept laser at ...
The vast expansion of protein sequence databases provides an opportunity for new protein design approaches which seek to learn the sequence-function relationship directly from natural sequence variation. Deep generative models trained on protein sequ...
In addition to helping develop products that aid the disabled, brain-computer interface (BCI) technology can also become a modality of entertainment for all people. However, most BCI games cannot be widely promoted due to the poor control performance...
AIM: To evaluate the suitability of a deep-learning (DL) algorithm for identifying normality as a rule-out test for fully automated diagnosis in frontal adult chest radiographs (CXR) in an active clinical pathway.
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