AIMC Topic: Deep Learning

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Novel Privacy Preserving Non-Invasive Sensing-Based Diagnoses of Pneumonia Disease Leveraging Deep Network Model.

Sensors (Basel, Switzerland)
This article presents non-invasive sensing-based diagnoses of pneumonia disease, exploiting a deep learning model to make the technique non-invasive coupled with security preservation. Sensing and securing healthcare and medical images such as X-rays...

Generalizing deep learning brain segmentation for skull removal and intracranial measurements.

Magnetic resonance imaging
Total intracranial volume (TICV) and posterior fossa volume (PFV) are essential covariates for brain volumetric analyses with structural magnetic resonance imaging (MRI). Detailed whole brain segmentation provides a non-invasive way to measure brain ...

DFpin: Deep learning-based protein-binding site prediction with feature-based non-redundancy from RNA level.

Computers in biology and medicine
The interaction between proteins and RNA is closely related to various human diseases. Computer-aided drug design can be facilitated by detecting the RNA sites that bind proteins. However, due to the aggregation of binding sites in RNA sequences, hig...

Robust asynchronous control of ERP-Based brain-Computer interfaces using deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Brain-computer interfaces (BCI) based on event-related potentials (ERP) are a promising technology for alternative and augmented communication in an assistive context. However, most approaches to date are synchronous, requir...

Classifying social determinants of health from unstructured electronic health records using deep learning-based natural language processing.

Journal of biomedical informatics
OBJECTIVE: Social determinants of health (SDOH) are non-medical factors that can profoundly impact patient health outcomes. However, SDOH are rarely available in structured electronic health record (EHR) data such as diagnosis codes, and more commonl...

Predicting SARS-CoV-2 infection duration at hospital admission:a deep learning solution.

Medical & biological engineering & computing
COVID-19 cases are increasing around the globe with almost 5 million of deaths. We propose here a deep learning model capable of predicting the duration of the infection by means of information available at hospital admission. A total of 222 patients...

An Efficient Deep Learning Approach to Automatic Glaucoma Detection Using Optic Disc and Optic Cup Localization.

Sensors (Basel, Switzerland)
Glaucoma is an eye disease initiated due to excessive intraocular pressure inside it and caused complete sightlessness at its progressed stage. Whereas timely glaucoma screening-based treatment can save the patient from complete vision loss. Accurate...

Automated segmentation of articular disc of the temporomandibular joint on magnetic resonance images using deep learning.

Scientific reports
Temporomandibular disorders are typically accompanied by a number of clinical manifestations that involve pain and dysfunction of the masticatory muscles and temporomandibular joint. The most important subgroup of articular abnormalities in patients ...

Quantifying the cell morphology and predicting biological behavior of signet ring cell carcinoma using deep learning.

Scientific reports
Signet ring cell carcinoma (SRCC) is a malignant tumor of the digestive system. This tumor has long been considered to be poorly differentiated and highly invasive because it has a higher rate of metastasis than well-differentiated adenocarcinoma. Bu...

Automated food intake tracking requires depth-refined semantic segmentation to rectify visual-volume discordance in long-term care homes.

Scientific reports
Malnutrition is a multidomain problem affecting 54% of older adults in long-term care (LTC). Monitoring nutritional intake in LTC is laborious and subjective, limiting clinical inference capabilities. Recent advances in automatic image-based food est...