AIMC Topic: Deep Learning

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Early Nephrosis Detection Based on Deep Learning with Clinical Time-Series Data.

Studies in health technology and informatics
Nephrosis is disease characterized by abnormal protein loss from impaired kidney. We constructed early prediction model using machine learning from clinical time series data, that can predict onset of nephrosis for more than one month. Long short-ter...

Development of Deep Learning Algorithm for Detection of Colorectal Cancer in EHR Data.

Studies in health technology and informatics
We aimed to develop a deep learning model for the prediction of the risk of advanced colorectal cancer in Taiwanese adults. We collected data of 58152 patients from the Taiwan National Health Insurance database from 1999 to 2013. All patients' comorb...

Impact of De-Identification on Clinical Text Classification Using Traditional and Deep Learning Classifiers.

Studies in health technology and informatics
Clinical text de-identification enables collaborative research while protecting patient privacy and confidentiality; however, concerns persist about the reduction in the utility of the de-identified text for information extraction and machine learnin...

Word Embedding for French Natural Language in Healthcare: A Comparative Study.

Studies in health technology and informatics
Structuring raw medical documents with ontology mapping is now the next step for medical intelligence. Deep learning models take as input mathematically embedded information, such as encoded texts. To do so, word embedding methods can represent every...

Update on thyroid ultrasound: a narrative review from diagnostic criteria to artificial intelligence techniques.

Chinese medical journal
OBJECTIVE: Ultrasound imaging is well known to play an important role in the detection of thyroid disease, but the management of thyroid ultrasound remains inconsistent. Both standardized diagnostic criteria and new ultrasound technologies are essent...

Development and Validation of a Deep Learning-based Automatic Detection Algorithm for Active Pulmonary Tuberculosis on Chest Radiographs.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
BACKGROUND: Detection of active pulmonary tuberculosis on chest radiographs (CRs) is critical for the diagnosis and screening of tuberculosis. An automated system may help streamline the tuberculosis screening process and improve diagnostic performan...

Tracheal Sound Analysis Using a Deep Neural Network to Detect Sleep Apnea.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
STUDY OBJECTIVES: Portable devices for home sleep apnea testing are often limited by their inability to discriminate sleep/wake status, possibly resulting in underestimations. Tracheal sound (TS), which can be visualized as a spectrogram, carries inf...

Promoter analysis and prediction in the human genome using sequence-based deep learning models.

Bioinformatics (Oxford, England)
MOTIVATION: Computational identification of promoters is notoriously difficult as human genes often have unique promoter sequences that provide regulation of transcription and interaction with transcription initiation complex. While there are many at...

DeepPhos: prediction of protein phosphorylation sites with deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Phosphorylation is the most studied post-translational modification, which is crucial for multiple biological processes. Recently, many efforts have been taken to develop computational predictors for phosphorylation site prediction, but m...